Estimating canopy closure density and above-ground tree biomass using partial least square methods in Chinese boreal forests

Boreal forests play an important role in global environment systems. Understanding boreal forest ecosystem structure and function requires accurate monitoring and estimating of forest canopy and biomass. We used partial least square regression （PLSR） models to relate forest parameters, i.e. canopy closure density and above ground tree biomass, to Landsat ETM＋ data. The established models were optimized according to the variable importance for projection （VIP） criterion and the bootstrap method, and their performance was compared using several statistical indices. All variables selected by the VIP criterion passed the bootstrap test （p〈0.05）. The simplified models without insignificant variables （VIP 〈1） performed as well as the full model but with less computation time. The relative root mean square error （RMSE%） was 29% for canopy closure density, and 58% for above ground tree biomass. We conclude that PLSR can be an effective method for estimating canopy closure density and above ground biomass.

Individual tree segmentation and biomass estimation based on UAV Digital aerial photograph

Digital aerial photograph(DAP)data is processed based on Structure from Motion(Sf M)algorithm and regional net adjustment method to generate digital surface discrete point clouds similar to Light Detection and Ranging(LiDAR)and digital orthophoto mosaic(DOM)similar to optical remote sensing image.In this study,we obtained highresolution images of mature forests of Chinese fir by unmanned aerial vehicle(UAV)flying through crossroute flight,and then reconstructed the threedimensional point clouds in the UAV aerial area by SfM technique.The point cloud segmentation(PCS)algorithm was used for the individual tree segmentation,and the F-score of the three sample plots were 0.91,0.94,and 0.94,respectively.Individual tree biomass modeling was conducted using 155 mature Chinese fir forests which were correctly segmented.The relative root mean squared error(rRMSE)values of random forest(RF),bagged tree(BT)and support vector regression(SVR)were 34.48%,35.74%and 40.93%,respectively.Our study demonstrated that DAP point clouds had great potential to extract forest vertical parameters and could be applied successfully in individual tree segmentation and individual tree biomass modeling.

Efficiency of Bio-Fertilizing as One of the Natural Alternatives to Improve the Growth of Khaya senegalensis and Swietenia mahagoni Trees and for Sustainability

A field experiment was carried out at Ismailia Research Station, Ismailia Governorate from 2020-2022 to improve the growth of Khaya senegalensis and Swietenia mahagoni by using a combination of mineral fertilizer (NPK) and biological fertilizer (Azotobacter chroococcum, Bacillus megatherium, and Bacillus circulant) as recommended dose under new sandy soils conditions. Split plot designed with four treatments (Control, (50% Mineral fertilizer (M.) + 50% Biological fertilizer (Bio.)), 100% M. and 100% Bio.) of each species. Vegetative growth, leaf area, tree biomass, stored carbon, basal area, tree volume, and in the soil both of microbial account and mineral content were determined. The experimental results showed no significant differences between studied species among the most studied parameters except for Khaya senegalensis which gave the highest significant difference in root biomass and below-stored carbon than Swietenia mahagoni. Evidently, the highest significant growth parameters were 100% mineral fertilizer followed by (50% M. + 50% Bio.) as compared with control. No significant difference between 100% M. and (50% M. + 50% Bio.) of shoot dry biomass (15.19 and 12.02 kg, respectively) and above-stored carbon (0.28 and 0.22 Mt, respectively). Microbial account and mineral content in soil were improved after cultivation of tree species compared to before planting and control, especially with 50% mineral fertilizer and 50% bio-fertilizer treatment. In conclusion, a treatment containing 50% mineral fertilizer and 50% bio-fertilizer has led to the ideal Khaya senegalensis and Swietenia mahagoni growth in sandy soil for cheaper and sustainable.

Quantification of Above-Ground Biomass and Carbon Sequestration Potential of Roadside Trees in the Plateau Department of Benin Republic

Roadside trees are effective natural solutions for mitigating climate change. Despite the usefulness of trees to carbon sequestration, there is a dearth of information on the estimation of biomass and carbon stock for roadside trees in the study area. This study aimed to estimate the carbon stock and carbon dioxide equivalent of roadside trees. A complete enumeration of trees was carried out in Kétou, Pobè and Sakété within the communes of the Plateau Department, Bénin Republic. Total height and diameter at breast height were measured from trees along the roads while individual wood density value was obtained from wood density database. The allometric method of biomass estimation was adopted for the research. The results showed that the total estimations for above-ground biomass, carbon stock and carbon equivalent from all the enumerated roadside trees were 154.53 mt, 72.63 mt and 266.55 mt, respectively. The results imply that the roadside trees contain a substantial amount of carbon stock that can contribute to climate change mitigation through carbon sequestration.

Assessing Biomass Expansion Factor of Birch Tree <i>Betula utilis</i>D. DON

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.

Forest Biomass Management challenges in Commercially Exotic Tree Plantations Areas. A case study from the Rungwe Volcanic Province (Southern Highlands of Tanzania)

The carbon (C) stored in the living biomass of trees is typically the largest C pool of the forest ecosystem which is directly impacted by deforestation and degradation (Ensslin et al, 2015). The relationships between diversity, biomass and C stocks at varied altitudes can have crucial implications for the management and conservation of C sinks. The study was conducted at Mbeya One ward lying between Mporoto and Rungwe forest reserves in Mbeya rural district, in the Southern highlands of Tanzania. The main objective was (1) to assess the indigenous tree biomass variation between Mporoto and Rungwe forest reserves (2) to assess the exotic tree biomass variation between the two forest reserves and (3) to assess the human implication on aboveground biomass variation between the two forest reserves. The findings indicated the significant decreased in indigenous trees biomass in residential and crop land areas with a hasty increase in biomass when reaching Mporoto forest reserve indicating little human encroachment in the forest reserve. There was the same trend towards Rungwe forest reserve however in that side, there was a slight increase in indigenous tree biomass when reaching forest reserve which is the sign of human encroachment in the forest reserve. The main human activities encroaching the reserve were;timber harvesting and commercial exotic trees planting (especially the commercial trees, Pinus patula sp). However, the trend was opposite for the exotic trees especially for Pinus patula and Eucalyptus sp in the study area. Hence the study concludes that there is a significant variation between indigenous and exotic trees in the study area, hence the variation in the tree biomass (fig 2&3). There is also a massive human encroachment for indigenous trees clearance in expense of exotic trees plantations towards and in Rungwe forest reserve. Therefore, the study would like to call for an urgent intervention especially in the east side of the study area (Rungwe forest reserve) stopping exotic tree plantation penetrating into the forest reserve which intensify cutting down of indigenous trees in the forest reserves plummeting aboveground biomass and escalating carbon emissions in the atmosphere while jeopardizing the natural forest ecosystem services to the communities. Conservation education should be emphasized in the study area to local communities, exotic trees plantations owners and other relevant stakeholders.

Carbon storage in biomass,litter,and soil of different native and introduced fast-growing tree plantations in the South Caspian Sea

Replantation of degraded forest using rapidgrowth trees can play a significant role in global carbon budget by storing large quantities of carbon in live biomass,forest floor,and soil organic matter.We assessed the potential of 20-year old stands of three rapid-growth tree species,including Alnus subcordata,Populus deltoides and Taxodium distichum,for carbon(C) storage at ecosystem level.In September 2013,48 replicate plots(16 m × 16 m) in 8 stands of three plantations were established.36 trees were felled down and fresh biomass of different components was weighed in the field.Biomass equations were fitted using data based on the 36 felled trees.The biomass of understory vegetation and litter were measured by harvesting all the components.The C fraction of understory,litter,and soil were measured.The ecosystem C storage was as follows: A.subcordata(626.5 Mg ha) [ P.deltoides(542.9Mg ha) [ T.distichum(486.8 Mg ha)(P \ 0.001),of which78.1–87.4% was in the soil.P.deltoides plantation reached the highest tree biomass(206.6 Mg ha),followed by A.subcordata(134.5 Mg ha) and T.distichum(123.3 Mg ha).The highest soil C was stored in theplantation of A.subcordata(555.5 Mg ha).The C storage and sequestration of the plantations after 20 years were considerable(25–30 Mg hayear) and broadleaves species had higher potential.Native species had a higher soil C storage while the potential of introduced species for live biomass production was higher.

Assessing the Biomass Potential of Major Industrial Tree Plantation Species for Green Energy Production

Energy requirements in both urban and rural areas are increasing giving added stress to the power generators and energy sources, thus blackouts are becoming common scenarios. Renewable energy from tree biomass is being eyed to provide solution to insufficient energy supply. A component of the green energy generation project is to assess the biomass potential of major industrial tree plantation species in the region at various ages, to determine the sustainability of a biomass-based green energy generation. Actual field measurements of biomass in selected plantations were conducted. In the field inventory, a plot measuring 10 × 50 meters was laid out randomly on the sampling site. For all trees inside the plot, the basal diameter and diameter at breast height for ages 1 to 2 years old and 3 to 5 years old, respectively were recorded. The results revealed that the biomass of major industrial tree species in Year 1 followed the order: Mangium (Acacia mangium) > Ipil-ipil (Leucaena leucocephala) > Falcata (Paraserianthes falcataria) > Bagras (Eucalyptus deglupta). However, as the trees mature, the biomass generation changed with Falcata overtaking Mangium. The order then was: Falcata (Paraserianthes falcataria) > Mangium (Acacia mangium) > Ipil-ipil (Leucaena leucocephala) > Bagras (Eucalyptus deglupta). Of the major industrial tree species, Falcata (Paraserianthes falcataria) and Mangium (Acacia mangium) are noted to have the biggest potential in supplying the biomass requirement of the green energy plant.

基于无人机低空遥感数据的时序动态生物量计算研究

为解决林分自然生长和人工剪伐修枝引起的单木特征参数变化所造成的生物量变化问题,采用地基激光雷达数据(TLS)和无人机激光雷达数据(UAV-LS)为数据源,通过单木分割的方法,以地基激光雷达数据提供的高精度数字高程模型为基础,提升无人机激光雷达数据的单木召回率;基于无人机激光雷达数据进行单木树高的提取及一致性评定,通过优化的生物量模型,利用树高参数计算2022年和2023年各树种单木生物量。结果表明,联合地面激光雷达数据可以将无人机激光雷达数据的单木召回率从60.0%提升至73.1%;对2022年、2023年树高参数提取得到近两年树木自然生长、修剪状况;对树高一致性评定得到一致性相关系数(Concordance correlation coefficient,CCC)为0.98,均方根误差(RMSE)为1.12 m;对生物量计算得到近两年各树种单木生物量、林分生物量,2022年、2023年单位面积生物量分别为77.39、81.56 t/hm^(2)。研究证实在研究区通过无人机低空遥感数据获取树高时序动态计算各树种单木生物量可行,可以掌握林分自然生长和人工修剪引起的生物量变化。

福建桉树异速生长方程与生物量估算

以中国南方主要速生丰产树种桉树为研究对象,利用野外破坏性实测的90棵桉树解析木数据,研究桉树单木器官生物量的分配及规律,构建最佳单木异速生长方程,计算桉树根冠比并将其应用于桉树树根生物量的估算。结果表明:1)桉树生物量的分配策略如下:随着林龄的增大,桉树树干的生物量分配比例不断增多,而树枝、树叶和树根的生物量分配比例不断减少。2)应用桉树分林龄的根冠比数据估算桉树树根生物量是最为可行且有效的方法。3)在桉树生物量的异速生长方程构建中,乘幂方程优于线性方程,最优自变量则根据各器官有所差异。

基于随机森林算法的桉树人工林单木生物量预估模型

单木生物量模型是估测森林生物量的基础。通过标准木法实测雷州半岛地区90株桉树单株生物量数据,随机划分60个样本数据作为训练集,30个样本数据作为验证集。以林龄、树高和胸径为自变量,单木生物量为因变量,使用岭回归模型、异速生长模型和随机森林算法构建模型,采用决定系数(R^(2))、均方根误差(RMSE)和平均绝对误差(MAE)对模型进行评价。结果表明:随机森林模型的R~2、RMSE和MAE无论在训练集还是验证集均高于岭回归模型和异速生长模型。由随机森林模型的因子重要值可知,胸径是影响单木生物量的主要因子。引入林龄因子后的随机森林模型可以提高单木生物量的预测精度,为碳汇计量提供基础数据和模型支撑。

Estimation of the carbon pool in soil and above-ground biomass within mangrove forests in Southeast Mexico using allometric equations

We report the results of carbon stored in soil and aboveground biomass from the most important area of mangroves in Mexico, with dominant vegetation of Red mangrove （Rhizophora mangle L.）, Black mangrove （Avicennia germinans L.）, white mangrove （Laguncularia racemosa Gaertn.） and button mangrove （Conocarpus erectus L.）. We sampled soils with high fertility during the dry season in 2009 and 2010 at three sites on Atasta Peninsula, Campeche. We used allometric equations to estimate above ground biomass （AGB） of trees. AGB was higher in C. erectus （253.18±32.17 t？ha-1）, lower in A. germinans （161.93±12.63 t？ha-1）, and intermediate in R. mangle （181.70±16.58 t？ha-1） and L. racemosa （206.07±19.12 t？ha-1）. Of the three studied sites, the highest absolute value for AGB was 279.72 t？ha-1 in button mangrove forest at any single site. Carbon stored in soil at the three sites ranged from 36.80±10.27 to 235.77±66.11 t？ha-1. The Tukey test （p 〈0.05） made for AGB was higher for black mangrove showed significant differences in soil carbon content between black mangrove and button mangrove. C. erectus had higher AGB compared with the other species. A. germinans trees had lower AGB because they grew in hypersaline environments, which reduced their development. C. erectus grew on higher ground where soils were richer in nutrients. AGB tended to be low in areas near the sea and increased with distance from the coast. A. germinans usually grew on recently deposited sediments. We assumed that all sites have the same potential to store carbon in soil, and then we found that there were no significant differences in carbon content between the three samples sites： all sites had potential to store carbon for long periods. Carbon storage at the three sampling sites in the state of Campeche, Mexico, was higher than that reported for other locations.

珍贵树种与桉树混交对生态系统生物量和碳储量的影响探析

[目的]探究珍贵树种和桉树混交造林对生态系统生物量和碳储量的影响。[方法]以广西黄冕林场为例,以桉树纯林(A1)、桉树和红锥混交林(A2)、桉树和荷木混交林(A3)为研究对象,分析不同林分下树种的密度及生长指标、生态系统的生物量、生态系统的碳储量情况。[结果]在生长指标方面,A2、A3中桉树的胸径、树高、胸高断面积均高于A1,差异显著。在生态系统总生物量方面,A2与A3均明显高于A1,差异显著。不同林分生态系统总碳储量方面,A2、A3明显高于A1,差异显著。[结论]为提高生态系统生物量和碳储量,可在林场造林时将珍贵树种与桉树混交,可进一步提高人工林建设质量,营造良好的种间相互作用关系,提高资源的有效性和利用率,珍贵树种和桉树混交造林后,生态系统的生物量和碳储量更高,可促进维持生态平衡。

青藏高原草地地上生物量估算

及时准确评估草地产草量对草地资源的科学管理和可持续发展具有重要意义。青藏高原自然环境特殊,气候差异显著,地形复杂,仅依靠遥感信息准确监测草地地上生物量(Aboveground Biomass,AGB)变化有较大限制。基于青藏高原草地AGB野外实测数据与Landsat遥感影像,探索了植被指数表征草地AGB信息的有效性,评估了气象和地形信息对准确估算草地AGB的影响,综合利用气象、地形和遥感信息,在新一代地球科学数据和分析应用平台(Google Earth Engine)上构建了梯度增强回归树草地AGB估算模型,绘制了青藏高原多年草地AGB空间分布图。结果表明:(1)基于单因素遥感因子的线性回归模型仅能解释8%—40%的草地AGB变化情况,其中绿色归一化植被指数(Green Normalized Difference Vegetation Index,GNDVI)对草地AGB解释能力较强(40%)。(2)基于遥感因子构建的梯度增强回归树模型测试集R~2为0.57。分别添加气象、地形信息,模型对草地AGB的估测准确性有所提升,测试R~2为0.62和0.63。(3)基于气象、地形和遥感因子的多因素估测模型能够提高草地AGB估测精度,经递归特征消除法优选后,基于13个特征变量的梯度增强回归树模型拟合效果最好(训练数据集R~2=0.79,RMSE=43.42 g/m^(2),P<0.01;测试数据集R~2=0.66,RMSE=53.64 g/m^(2),P<0.01),可以解释66%草地AGB变化情况。(4)2010年青藏高原平均AGB为94.58 g/m^(2),2015年93.63 g/m^(2),2020年100.78 g/m^(2)。青藏高原西北部草地AGB较低,东南部草地AGB较高,整体呈现自西北向东南逐渐增加的分布格局。研究结果为准确估算青藏高原草地产草量和碳储量等研究提供重要参考。

南方典型红壤侵蚀区马尾松林立木生物量无人机遥感估测

以南方典型红壤侵蚀区长汀县河田镇为例,结合无人机与激光雷达产生的点云数据优势,通过局部最大值和分水岭算法反演单木树高(H)和冠层半径(R_(c)),拟合以H和R_(c)为变量组合的异速生长方程,得到以新冠层参数为底的马尾松立木生物量模型。结果表明:提取树高的决定系数(R^(2))和均方根误差(RMSE)分别为0.93和0.49 m;计算冠层半径的R2和RMSE分别为0.88和0.64 m;估算立木生物量的R^(2)和RMSE分别为0.89和3.37 kg。本研究通过无人机遥感影像定量参数并构建的异速生长方程中,以组合(H+R_(c))为底的异速生长方程估测马尾松林立木生物量的精度较高,可以有效估测马尾松林立木生物量,可为南方典型红壤侵蚀区马尾松林立木生物量准确估测提供参考。

大花紫薇幼苗对水分胁迫及解除的生长响应

[目的]分析不同水分处理对抗性树种大花紫薇Lagerstroemia speciosa生长的影响,探究大花紫薇形态性状的响应机制,为抗性园林树种的选择及水分管理提供理论依据。[方法]以大花紫薇的1年生幼苗为材料,设置干旱(DR)、水淹(WL)、水淹-干旱交叉(WD)和对照(正常浇水,CK) 4种水分处理,开展30 d水分胁迫试验,随后解除水分胁迫,并维持DR、WL、WD处理组植株的土壤水分在CK水平,进行为期30 d的恢复生长,测定水分胁迫及解除后植株的叶性状、根系性状和生物量指标。[结果]DR、WD胁迫终期和WL恢复终期的总叶面积相较CK显著下降;3种水分胁迫处理的叶组织密度在胁迫终期相较CK显著上升,比叶面积在恢复终期显著下降。胁迫终期时,WL和WD处理提升了细根根长占比和细根表面积占比;恢复终期时,DR、WL、WD处理的细根表面积占比分别比CK升高了9.59%、12.42%、13.57%;胁迫终期和恢复终期时,WL处理的比根长和比根面积显著高于CK。胁迫终期时,3种水分胁迫下的植株增加了对茎的生物量分配,且WL处理植株生长的不定根占总根系生物量的26.95%;DR胁迫终期和恢复终期的根系生物量分配显著升高,根冠比分别相比各自CK提升了40.93%和70.06%。相关性分析表明,叶性状间、根系性状间分别存在权衡关系;根长、根表面积与叶组织密度呈显著正相关。[结论]大花紫薇叶-根系性状间存在一定的相关性;短期的水分胁迫对大花紫薇幼苗根系生长具促进作用,使其更好地适应城市园林绿地复杂多变的水环境。

6种阔叶树种幼苗生物量分配特征及模型构建

以福建省上杭白砂国有林场闽楠、南岭栲、米老排、青冈、云山青冈和木荷2年生幼苗为研究对象,采用全株收获法获取6种树种幼苗根、茎、叶及整株的生物量,比较其分配特征和地上、地下生物量的异速生长关系,建立不同树种幼苗各器官及整株生物量的回归估测模型。结果表明:(1)不同树种幼苗整株生物量差异显著,依次为青冈>米老排>南岭栲>云山青冈>木荷>闽楠。(2)不同树种幼苗各器官生物量分配差异显著,其中青冈根生物量占比最大(39.9%),米老排茎生物量占比最大(45.0%),闽楠叶生物量占比最大(49.2%)。(3)不同树种幼苗地下生物量与地上生物量比值均小于1,表明幼苗生物量更多地分配到茎和叶。除木荷外,其余树种地上、地下生物量均遵循显著的等速生长关系。(4)不同树种幼苗生物量回归估测模型多为幂函数模型,其次为三次多项式模型。6种树种幼苗整株生物量在不同器官分配上存在差异,同时幼苗地上、地下生物量间呈现出等速生长规律。各树种幼苗生物量回归估测模型拟合效果较好,可在相同或相似立地条件下估算不同树种幼苗生物量。

Low net primary productivity of dominant tree species in a karst forest, southwestern China： first evidences from tree ring width and girth increment

Aboveground net primary productivity(ANPP)of two dominant species, one deciduous tree(Platycarya strobilacea) and one evergreen tree(Machilus cavaleriei),was estimated based on the tree-ring width and the girth increment as well as allometric functions in a karst evergreen and deciduous broadleaved mixed forest in central Guizhou Province, southwestern China. Results showed that the ANPP increased from 1961 to 2015, especially during the last 20–30 years, but with strong variations. The deciduous tree had higher ANPP than the evergreen tree according to two kinds of estimates by the tree ring and girth increment. The averaged ANPP for these two mature trees was 2.27 kg/individual/year, ca. 8 t/ha/year considering the normal stand density. Such karst forest productivity was lower than the natural subtropical forests in China and in the world.

Variations in the biomass of Eucalyptus plantations at a regional scale in Southern China

We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method（BEF） versus estimates obtained from a local biomass model,based on large-scale empirical field inventory sampling data.The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method.Relative to the local model,BEF overestimated accumulative biomass by 22.12%.The predominant sources of the total deviation （70.94%） were stand-structure variables.Stand age and diameter at breast height are the major factors.Compared with biotic variables,abiotic variables had a smaller overall contribution （29.06%）,with elevation and soil depth being the most important among the examined abiotic factors.Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data.To minimize deviations,stand age and elevation should be included in regional forest-biomass estimation.