Background:National and international institutions periodically demand information on forest indicators that are used for global reporting.Among other aspects,the carbon accumulated in the biomass of forest species mu...Background:National and international institutions periodically demand information on forest indicators that are used for global reporting.Among other aspects,the carbon accumulated in the biomass of forest species must be reported.For this purpose,one of the main sources of data is the National Forest Inventory(NFI),which together with statistical empirical approaches and updating procedures can even allow annual estimates of the requested indicators.Methods:Stand level biomass models,relating the dry weight of the biomass with the stand volume were developed for the five main pine species in the Iberian Peninsula(Pinus sylvestris,Pinus pinea,Pinus halepensis,Pinus nigra and Pinus pinaster).The dependence of the model on aridity and/or mean tree size was explored,as well as the importance of including the stand form factor to correct model bias.Furthermore,the capability of the models to estimate forest carbon stocks,updated for a given year,was also analysed.Results:The strong relationship between stand dry weight biomass and stand volume was modulated by the mean tree size,although the effect varied among the five pine species.Site humidity,measured using the Martonne aridity index,increased the biomass for a given volume in the cases of Pinus sylvestris,Pinus halepensis and Pinus nigra.Models that consider both mean tree size and stand form factor were more accurate and less biased than those that do not.The models developed allow carbon stocks in the main Iberian Peninsula pine forests to be estimated at stand level with biases of less than 0.2 Mg·ha^(-1).Conclusions:The results of this study reveal the importance of considering variables related with environmental conditions and stand structure when developing stand dry weight biomass models.The described methodology together with the models developed provide a precise tool that can be used for quantifying biomass and carbon stored in the Spanish pine forests in specific years when no field data are available.展开更多
Species specific allometric equations are important for estimation and quantification of net volume and aboveground biomass of living trees. This study was basically focused on fitting total volume and aboveground bio...Species specific allometric equations are important for estimation and quantification of net volume and aboveground biomass of living trees. This study was basically focused on fitting total volume and aboveground biomass models for Juniperus procera plantations in Wondo Genet, Sidama Zone, Ethiopia. Data for fitting the total volume and aboveground biomass models were obtained by destructively sampling of trees from the ten diameter classes of the Juniperus procera plantation in the study area. A total of one hundred ten and fifty-one trees were destructively sampled to fit six total volume and six aboveground biomass models respectively. After important measurements of parameters have completed, model performance evaluation and selecting of best fit models were undertaken using standard error of estimates (SEE), coefficient of determination (R2), bias (B) and mean of the absolute value of errors (MAE). Accordingly, the total volume model Vt = -5.466 + 0.959Dbh0.005H003 and aboveground biomass model of B = 0.348Dbh0.57H0.032 were found to be the best predictive models for total tree volume and aboveground biomass respectively. In addition to the above results, diameter at breast height and total tree height data obtained from 69 circular sample plots of 0.01 ha area drawn from the plantation were used to estimate the total volume and aboveground biomass per hectare BEF which was estimated to be 0.64 Mg/m3. Generally, the selected models and computed BEF in this study are believed to be applied by different organisations and researches to estimate the total volume and aboveground biomass of the J. procera.展开更多
Biomass is the component of living organism and mostly obtained from plants, animals, insects and the residue of all the mentioned organisms. Biomass is the key source of energy present in the form of organic matter. ...Biomass is the component of living organism and mostly obtained from plants, animals, insects and the residue of all the mentioned organisms. Biomass is the key source of energy present in the form of organic matter. The study aimed to find out biomass and its variation in each component of Betula utilis D. Don (Birch Tree) with varying diameter at Kalam forest division Swat, Khyber Pakhtunkhwa (KPK) province, Pakistan. The biomass of different components was determined by non-destructive methods. Overall, 30 trees were selected from different diameter classes viz a viz up to 10, 11 - 20 and greater than 20 cm. Ten trees were selected from each class. The diameter of stem and large branches and their length were measured in the field. Later, the volumes of stem and branches were calculated and converted into biomass. The study revealed that stem contributes 42.65% biomass followed by large and sub branches as 39.22% and 13.54% respectively. Leaves contribute 4.59% only. The above tree biomass contribution by different components was arranged as stem was greater than large branches;these were greater than sub branches and the lowest was in leaves. The total above ground biomass of single tree was 20.59, 58.041 and 197.214 kg·tree-1 respectively for diameter up to 10, 11 - 20 and greater than 20 cm. The averaged biomass in all diameter classes was 91.95 ± 93.064 kg·tree-1. The total biomass of single tree of diameter class up to 10, 11 - 20 and greater than 20 cm was 24.71, 69.649 and 236 kg respectively. The below ground biomass of single tree of diameter class up to 10, 11 - 20 and greater than 20 cm was 4.11 ± 1.24 kg, 11.61 ± 3.56 kg and 39.44 ± 8.9 kg respectively. The biomass expansion factor was 1.34, 1.47, and 1.5 t·m-3 respectively for diameter classes up to 10 cm, 11 - 20 cm and greater than 20 cm respectively. The mean biomass expansion factor for all diameter classes was 1.44 t·m-3.展开更多
Addressing climate change has become a common issue around the world in the 21st century and equally an important mission in Chinese forestry.Understanding the development of monitoring and assessment of forest biomas...Addressing climate change has become a common issue around the world in the 21st century and equally an important mission in Chinese forestry.Understanding the development of monitoring and assessment of forest biomass and carbon storage in China is important for promoting the evaluation of forest carbon sequestration capacity of China.The author conducts a systematic analysis of domestic publications addressing＂monitoring and assessment of forest biomass and carbon storage＂in order to understand the development trends,describes the brief history through three stages,and gives the situation of new development.Towards the end of the 20th century,a large number of papers on biomass and productivity of the major forest types in China had been published,covering the exploration and efforts of more than 20 years,while investigations into assessment of forest carbon storage had barely begun.Based on the data of the 7th and 8th National Forest Inventories,forest biomass and carbon storage of the entire country were assessed using individual tree biomass models and carbon conversion factors of major tree species,both previously published and newly developed.Accompanying the implementation of the 8th National Forest Inventory,a program of individual tree biomass modeling for major tree species in China was carried out simultaneously.By means of thematic research on classification of modeling populations,as well as procedures for collecting samples and methodology for biomass modeling,two technical regulations on sample collection and model construction were published as ministerial standards for application.Requests for approval of individual tree biomass models and carbon accounting parameters of major tree species have been issued for approval as ministerial standards.With the improvement of biomass models and carbon accounting parameters,thematic assessment of forest biomass and carbon storage will be gradually changed into a general monitoring of forest biomass and carbon storage,in order to realize their dynamic monitoring in national forest inventories.Strengthening the analysis and assessment of spatial distribution patterns of forest biomass and carbon storage through application of remote sensing techniques and geostatistical approaches will also be one of the major directions of development in the near future.展开更多
Estimating individual tree biomass is critical to forest carbon accounting and ecosystem service modeling.In this study,we developed one-（tree diameter only） and two-variable（tree diameter and height） biomass equa...Estimating individual tree biomass is critical to forest carbon accounting and ecosystem service modeling.In this study,we developed one-（tree diameter only） and two-variable（tree diameter and height） biomass equations,biomass conversion factor（BCF） models,and an integrated simultaneous equation system（ISES） to estimate the aboveground biomass for five conifer species in China,i.e.,Cunninghamia lanceolata（Lamb.） Hook.,Pinus massoniana Lamb.,P.yunnanensis Faranch,P.tabulaeformis Carr.and P.elliottii Engelm.,based on the field measurement data of aboveground biomass and stem volumes from 1055 destructive sample trees across the country.We found that all three methods,including the one-and two-variable equations,could adequately estimate aboveground biomass with a mean prediction error less than 5%,except for Pinus yunnanensis which yielded an error of about 6%.The BCF method was slightly poorer than the biomass equation and the ISES methods.The average coefficients of determination（R^2） were 0.944,0.938 and 0.943 and the mean prediction errors were 4.26,4.49 and 4.29% for the biomass equation method,the BCF method and the ISES method,respectively.The ISES method was the best approach for estimating aboveground biomass,which not only had high accuracy but also could estimate stocking volumes simultaneously that was compatible with aboveground biomass.In addition,we found that it is possible to develop a species-invariant one-variable allometric model for estimating aboveground biomass of all the five coniferous species.The model had an exponent parameter of 7/3 and the intercept parameter a_0 could be estimated indirectly from stem basic density（a_0= 0.294 q）.展开更多
通过整理归纳落叶松(Larix)天然林和人工林的生物量文献数据,研究探讨了有关生物量碳计量参数,结果表明:1)落叶松生物量转化与扩展因子(Biomass conversion and expansionfactor,BCEF)的平均值为0.6834Mg.m-3(n=113,SD=0.3551),其中天...通过整理归纳落叶松(Larix)天然林和人工林的生物量文献数据,研究探讨了有关生物量碳计量参数,结果表明:1)落叶松生物量转化与扩展因子(Biomass conversion and expansionfactor,BCEF)的平均值为0.6834Mg.m-3(n=113,SD=0.3551),其中天然林为0.5551Mg.m-3(n=56,SD=0.0582),明显小于人工林的0.8095Mg.m-3(n=57,SD=0.4650)(p<0.05);生物量扩展因子(Biomass expansion factor,BEF)的平均值为1.3493(n=134,SD=0.3844),其中天然林为1.1763(n=63,SD=0.0399),也明显小于人工林的1.5029(n=71,SD=0.4780)(p<0.05)。天然林与人工林的BCEF和BEF随林龄(Stand age,A)、平均胸径(Diameter at breast height,DBH)和林分密度(Stand density,D)的增加呈现相反的变化趋势。天然林的BCEF和BEF随A和DBH的增加而增加,随D的增加而呈降低趋势。人工林随A和DBH的增加呈指数降低并趋于稳定值,随D的增加而呈增加趋势。2)根茎比(Root∶shoot ratio,R)的平均值为0.2456(n=156,SD=0.0926),其中天然林为0.2376(n=64,SD=0.0618)),人工林为0.2511(n=92,SD=0.1090),二者无明显差异(p<0.05)。天然林的R随A和DBH的增加分别呈明显的指数和幂函数增加,而随D的增加呈幂函数下降,而人工林的R与A、DBH和D没有显著相关性(p<0.05)。3)群落生物量扩展因子(Community biomass expansionfactor,CBEF)的平均值为1.0792(n=49,SD=0.1005),其中天然林为1.1039(n=29,SD=0.1149),明显大于人工林的1.0434(n=20,SD=0.0614)(p<0.05)。由于天然林和人工林的某些碳计量参数(如BCEF、BEF、CBEF)间存在明显差异,在进行落叶松林生物量碳计量时需分别天然林和人工林计算,在使用有关参数时还需考虑A、DBH和D等因素,有利于降低计量中的不确定性。但是人工林的有些参数(如人工林BCEF和BEF与D的关系、天然林和人工林的CBEF等)尚需进一步研究。展开更多
文摘Background:National and international institutions periodically demand information on forest indicators that are used for global reporting.Among other aspects,the carbon accumulated in the biomass of forest species must be reported.For this purpose,one of the main sources of data is the National Forest Inventory(NFI),which together with statistical empirical approaches and updating procedures can even allow annual estimates of the requested indicators.Methods:Stand level biomass models,relating the dry weight of the biomass with the stand volume were developed for the five main pine species in the Iberian Peninsula(Pinus sylvestris,Pinus pinea,Pinus halepensis,Pinus nigra and Pinus pinaster).The dependence of the model on aridity and/or mean tree size was explored,as well as the importance of including the stand form factor to correct model bias.Furthermore,the capability of the models to estimate forest carbon stocks,updated for a given year,was also analysed.Results:The strong relationship between stand dry weight biomass and stand volume was modulated by the mean tree size,although the effect varied among the five pine species.Site humidity,measured using the Martonne aridity index,increased the biomass for a given volume in the cases of Pinus sylvestris,Pinus halepensis and Pinus nigra.Models that consider both mean tree size and stand form factor were more accurate and less biased than those that do not.The models developed allow carbon stocks in the main Iberian Peninsula pine forests to be estimated at stand level with biases of less than 0.2 Mg·ha^(-1).Conclusions:The results of this study reveal the importance of considering variables related with environmental conditions and stand structure when developing stand dry weight biomass models.The described methodology together with the models developed provide a precise tool that can be used for quantifying biomass and carbon stored in the Spanish pine forests in specific years when no field data are available.
文摘Species specific allometric equations are important for estimation and quantification of net volume and aboveground biomass of living trees. This study was basically focused on fitting total volume and aboveground biomass models for Juniperus procera plantations in Wondo Genet, Sidama Zone, Ethiopia. Data for fitting the total volume and aboveground biomass models were obtained by destructively sampling of trees from the ten diameter classes of the Juniperus procera plantation in the study area. A total of one hundred ten and fifty-one trees were destructively sampled to fit six total volume and six aboveground biomass models respectively. After important measurements of parameters have completed, model performance evaluation and selecting of best fit models were undertaken using standard error of estimates (SEE), coefficient of determination (R2), bias (B) and mean of the absolute value of errors (MAE). Accordingly, the total volume model Vt = -5.466 + 0.959Dbh0.005H003 and aboveground biomass model of B = 0.348Dbh0.57H0.032 were found to be the best predictive models for total tree volume and aboveground biomass respectively. In addition to the above results, diameter at breast height and total tree height data obtained from 69 circular sample plots of 0.01 ha area drawn from the plantation were used to estimate the total volume and aboveground biomass per hectare BEF which was estimated to be 0.64 Mg/m3. Generally, the selected models and computed BEF in this study are believed to be applied by different organisations and researches to estimate the total volume and aboveground biomass of the J. procera.
文摘Biomass is the component of living organism and mostly obtained from plants, animals, insects and the residue of all the mentioned organisms. Biomass is the key source of energy present in the form of organic matter. The study aimed to find out biomass and its variation in each component of Betula utilis D. Don (Birch Tree) with varying diameter at Kalam forest division Swat, Khyber Pakhtunkhwa (KPK) province, Pakistan. The biomass of different components was determined by non-destructive methods. Overall, 30 trees were selected from different diameter classes viz a viz up to 10, 11 - 20 and greater than 20 cm. Ten trees were selected from each class. The diameter of stem and large branches and their length were measured in the field. Later, the volumes of stem and branches were calculated and converted into biomass. The study revealed that stem contributes 42.65% biomass followed by large and sub branches as 39.22% and 13.54% respectively. Leaves contribute 4.59% only. The above tree biomass contribution by different components was arranged as stem was greater than large branches;these were greater than sub branches and the lowest was in leaves. The total above ground biomass of single tree was 20.59, 58.041 and 197.214 kg·tree-1 respectively for diameter up to 10, 11 - 20 and greater than 20 cm. The averaged biomass in all diameter classes was 91.95 ± 93.064 kg·tree-1. The total biomass of single tree of diameter class up to 10, 11 - 20 and greater than 20 cm was 24.71, 69.649 and 236 kg respectively. The below ground biomass of single tree of diameter class up to 10, 11 - 20 and greater than 20 cm was 4.11 ± 1.24 kg, 11.61 ± 3.56 kg and 39.44 ± 8.9 kg respectively. The biomass expansion factor was 1.34, 1.47, and 1.5 t·m-3 respectively for diameter classes up to 10 cm, 11 - 20 cm and greater than 20 cm respectively. The mean biomass expansion factor for all diameter classes was 1.44 t·m-3.
基金funded by the State Forestry Administration of China
文摘Addressing climate change has become a common issue around the world in the 21st century and equally an important mission in Chinese forestry.Understanding the development of monitoring and assessment of forest biomass and carbon storage in China is important for promoting the evaluation of forest carbon sequestration capacity of China.The author conducts a systematic analysis of domestic publications addressing＂monitoring and assessment of forest biomass and carbon storage＂in order to understand the development trends,describes the brief history through three stages,and gives the situation of new development.Towards the end of the 20th century,a large number of papers on biomass and productivity of the major forest types in China had been published,covering the exploration and efforts of more than 20 years,while investigations into assessment of forest carbon storage had barely begun.Based on the data of the 7th and 8th National Forest Inventories,forest biomass and carbon storage of the entire country were assessed using individual tree biomass models and carbon conversion factors of major tree species,both previously published and newly developed.Accompanying the implementation of the 8th National Forest Inventory,a program of individual tree biomass modeling for major tree species in China was carried out simultaneously.By means of thematic research on classification of modeling populations,as well as procedures for collecting samples and methodology for biomass modeling,two technical regulations on sample collection and model construction were published as ministerial standards for application.Requests for approval of individual tree biomass models and carbon accounting parameters of major tree species have been issued for approval as ministerial standards.With the improvement of biomass models and carbon accounting parameters,thematic assessment of forest biomass and carbon storage will be gradually changed into a general monitoring of forest biomass and carbon storage,in order to realize their dynamic monitoring in national forest inventories.Strengthening the analysis and assessment of spatial distribution patterns of forest biomass and carbon storage through application of remote sensing techniques and geostatistical approaches will also be one of the major directions of development in the near future.
基金funded by National Natural Science Foundation of China(Grant Nos.31270697,31370634,31570628)supported by State Forestry Administration of China(Grant No.2030208)
文摘Estimating individual tree biomass is critical to forest carbon accounting and ecosystem service modeling.In this study,we developed one-（tree diameter only） and two-variable（tree diameter and height） biomass equations,biomass conversion factor（BCF） models,and an integrated simultaneous equation system（ISES） to estimate the aboveground biomass for five conifer species in China,i.e.,Cunninghamia lanceolata（Lamb.） Hook.,Pinus massoniana Lamb.,P.yunnanensis Faranch,P.tabulaeformis Carr.and P.elliottii Engelm.,based on the field measurement data of aboveground biomass and stem volumes from 1055 destructive sample trees across the country.We found that all three methods,including the one-and two-variable equations,could adequately estimate aboveground biomass with a mean prediction error less than 5%,except for Pinus yunnanensis which yielded an error of about 6%.The BCF method was slightly poorer than the biomass equation and the ISES methods.The average coefficients of determination（R^2） were 0.944,0.938 and 0.943 and the mean prediction errors were 4.26,4.49 and 4.29% for the biomass equation method,the BCF method and the ISES method,respectively.The ISES method was the best approach for estimating aboveground biomass,which not only had high accuracy but also could estimate stocking volumes simultaneously that was compatible with aboveground biomass.In addition,we found that it is possible to develop a species-invariant one-variable allometric model for estimating aboveground biomass of all the five coniferous species.The model had an exponent parameter of 7/3 and the intercept parameter a_0 could be estimated indirectly from stem basic density（a_0= 0.294 q）.
文摘通过整理归纳落叶松(Larix)天然林和人工林的生物量文献数据,研究探讨了有关生物量碳计量参数,结果表明:1)落叶松生物量转化与扩展因子(Biomass conversion and expansionfactor,BCEF)的平均值为0.6834Mg.m-3(n=113,SD=0.3551),其中天然林为0.5551Mg.m-3(n=56,SD=0.0582),明显小于人工林的0.8095Mg.m-3(n=57,SD=0.4650)(p<0.05);生物量扩展因子(Biomass expansion factor,BEF)的平均值为1.3493(n=134,SD=0.3844),其中天然林为1.1763(n=63,SD=0.0399),也明显小于人工林的1.5029(n=71,SD=0.4780)(p<0.05)。天然林与人工林的BCEF和BEF随林龄(Stand age,A)、平均胸径(Diameter at breast height,DBH)和林分密度(Stand density,D)的增加呈现相反的变化趋势。天然林的BCEF和BEF随A和DBH的增加而增加,随D的增加而呈降低趋势。人工林随A和DBH的增加呈指数降低并趋于稳定值,随D的增加而呈增加趋势。2)根茎比(Root∶shoot ratio,R)的平均值为0.2456(n=156,SD=0.0926),其中天然林为0.2376(n=64,SD=0.0618)),人工林为0.2511(n=92,SD=0.1090),二者无明显差异(p<0.05)。天然林的R随A和DBH的增加分别呈明显的指数和幂函数增加,而随D的增加呈幂函数下降,而人工林的R与A、DBH和D没有显著相关性(p<0.05)。3)群落生物量扩展因子(Community biomass expansionfactor,CBEF)的平均值为1.0792(n=49,SD=0.1005),其中天然林为1.1039(n=29,SD=0.1149),明显大于人工林的1.0434(n=20,SD=0.0614)(p<0.05)。由于天然林和人工林的某些碳计量参数(如BCEF、BEF、CBEF)间存在明显差异,在进行落叶松林生物量碳计量时需分别天然林和人工林计算,在使用有关参数时还需考虑A、DBH和D等因素,有利于降低计量中的不确定性。但是人工林的有些参数(如人工林BCEF和BEF与D的关系、天然林和人工林的CBEF等)尚需进一步研究。
