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.

Differential roles of seed and sprout regeneration in forest diversity and productivity after disturbance

Natural regeneration after disturbances is a key phase of forest development,which determines the trajectory of successional changes in tree species composition and diversity.Regenerating trees can originate from either seeds or sprouts produced by disturbed trees with sprouting ability.Although both regeneration strategies often develop and co-occur after a disturbance,they tend to affect forest development differently due to significant functional differences.However,the origin of tree regeneration is rarely distinguished in post-disturbance forest surveys and ecological studies,and the differential roles of seed and sprout regeneration in forest productivity and diversity remain poorly understood.To address these research gaps,we explored the role of sprout and seed regeneration in the formation of woody species diversity and above-ground biomass(AGB)productivity in early-stage forest development.Data were collected in two experimental forest stands in the Czech Republic,where trees were cut with varying intensities with the density of residual(uncut)trees ranging from 0 to 275 trees per hectare.All trees were mapped and their sizes were measured before cutting and then,either as a stump with sprouts or a residual tree,remeasured 11 years later.In addition,all tree saplings were mapped and measured 11 years after logging,and their origin(sprout or seed)was identified.To assess abundances and productivity,we estimated AGB of all2,685 sprouting stumps of 19 woody species and 504 generative(i.e.,seed origin)individuals of 16 woody species,using allometric equations.Mixed-effects models were used to analyze the effects of each regeneration strategy on woody species diversity and the total AGB under varying densities of residual trees.Nonmetric multidimensional scaling was used to evaluate the effect of regeneration strategies on species composition.AGB and diversity of sprouts were significantly higher than those of seed regeneration.Sprouts formed on average97.1%of the total regeneration AGB in H ady and 98.6%in Sobe s ice.The average species richness of sprouts was4.7 in H ady and 2.2 in Sob e sice,while the species richness of seed regeneration averaged 2.1 and 1.1 in H ady and Sob e sice,respectively.Increasing density of residual trees reduced AGB and diversity of both sprouts and seed regeneration,but seed regeneration was affected to a greater extent.Residual trees had an especially strong inhibitory effect on the establishment of seed regeneration.Consequently,seed-originated saplings were nearly absent in plots with high residual tree density,and abundant sprouts accounted for most of the AGB and diversity.However,unlike sprouts whose species composition resembled that of the original stand,seed regeneration brought in new species,enriching the stand?s overall species pool and beta diversity.Our results demonstrated differential roles of sprout and seed regeneration in the early stage of forest succession.Sprout regeneration was the main source of woody AGB productivity as well as species diversity,and its importance increased with the increasing density of standing mature trees.The results indicate the crucial yet previously underestimated role of sprout regeneration in post-disturbance forest dynamics.They suggest that the presence of residual mature trees,whether retained after partial cutting or undisturbed,can substantially suppress seed regeneration while the role of sprout regeneration in early succession becomes more distinctly evident.

Biomass and dominance of conservative species drive above-ground biomass productivity in a mediterranean-type forest of Chile

Background: Forest productivity has a pivotal role in human well-being. Vegetation quantity, niche complementarity, mass-ratio, and soil resources are alternative/complementary ecological mechanisms driving productivity. One challenge in current forest management depends on identifying and manipulating these mechanisms to enhance productivity. This study assessed the extent to which these mechanisms control aboveground biomass productivity(AGBP) of a Chilean mediterranean-type matorral. AGBP measured as tree aboveground biomass changes over a 7-years period, was estimated for twelve 25 m × 25 m plots across a wide range of matorral compositions and structures. Variables related to canopy structure, species and functional diversity, species and functional dominance, soil texture, soil water and soil nitrogen content were measured as surrogates of the four mechanisms proposed. Linear regression models were used to test the hypotheses. A multimodel inference based on the Akaike’s information criterion was used to select the best models explaining AGBP and for identifying the relative importance of each mechanism.Results: Vegetation quantity(tree density) and mass-ratio(relative biomass of Cryptocarya alba, a conservative species) were the strongest drivers increasing AGBP, while niche complementarity(richness species) and soil resources(sand, %) had a smaller effect either decreasing or increasing AGBP, respectively. This study provides the first assessment of alternative mechanisms driving AGBP in mediterranean forests of Chile. There is strong evidence suggesting that the vegetation quantity and mass-ratio mechanisms are key drivers of AGBP, such as in other tropical and temperate forests. However, in contrast with other studies from mediterranean-type forests, our results show a negative effect of species diversity and a small effect of soil resources on AGBP.Conclusion: AGBP in the Chilean matorral depends mainly on the vegetation quantity and mass-ratio mechanisms.The findings of this study have implications for matorral restoration and management for the production of timber and non-timber products and carbon sequestration.

Estimating above-ground biomass by fusion of LiDAR and multispectral data in subtropical woody plant communities in topographically complex terrain in North-eastern Australia

We investigated a strategy to improve predicting capacity of plot-scale above-ground biomass （AGB） by fusion of LiDAR and Land- sat5 TM derived biophysical variables for subtropical rainforest and eucalypts dominated forest in topographically complex landscapes in North-eastern Australia. Investigation was carried out in two study areas separately and in combination. From each plot of both study areas, LiDAR derived structural parameters of vegetation and reflectance of all Landsat bands, vegetation indices were employed. The regression analysis was carded out separately for LiDAR and Landsat derived variables indi- vidually and in combination. Strong relationships were found with LiDAR alone for eucalypts dominated forest and combined sites compared to the accuracy of AGB estimates by Landsat data. Fusing LiDAR with Landsat5 TM derived variables increased overall performance for the eucalypt forest and combined sites data by describing extra variation （3% for eucalypt forest and 2% combined sites） of field estimated plot-scale above-ground biomass. In contrast, separate LiDAR and imagery data, andfusion of LiDAR and Landsat data performed poorly across structurally complex closed canopy subtropical minforest. These findings reinforced that obtaining accurate estimates of above ground biomass using remotely sensed data is a function of the complexity of horizontal and vertical structural diversity of vegetation.

Global patterns in above-ground net primary production and precipitation-use efficiency in grasslands

The above-ground net primary production(ANPP) and the precipitation-use efficiency(PUE) regulate the carbon and water cycles in grassland ecosystems, but the relationships among the ANPP, PUE and precipitation are still controversial. We selected 717 grassland sites with ANPP and mean annual precipitation(MAP) data from 40 publications to characterize the relationships ANPP–MAP and PUE–MAP across different grassland types. The MAP and ANPP showed large variations across all grassland types, ranging from 69 to 2335 mm and 4.3 to 1706 g m^(-2), respectively. The global maximum PUE ranged from 0.19 to 1.49 g m^(-2) mm^(-1) with a unimodal pattern. Analysis using the sigmoid function explained the ANPP–MAP relationship best at the global scale. The gradient of the ANPP–MAP graph was small for arid and semi-arid sites(MAP <400 mm). This study improves our understanding of the relationship between ANPP and MAP across dry grassland ecosystems. It provides new perspectives on the prediction and modeling of variations in the ANPP for different grassland types along precipitation gradients.

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.

Model-based estimation of above-ground biomass in the miombo ecoregion of Zambia

Background：Information on above-ground biomass（AGB） is important for managing forest resource use at local levels,land management planning at regional levels,and carbon emissions reporting at national and international levels.In many tropical developing countries,this information may be unreliable or at a scale too coarse for use at local levels.There is a vital need to provide estimates of AGB with quantifiable uncertainty that can facilitate land use management and policy development improvements.Model-based methods provide an efficient framework to estimate AGB.Methods：Using National Forest Inventory（NFI） data for a^1,000,000 ha study area in the miombo ecoregion,Zambia,we estimated AGB using predicted canopy cover,environmental data,disturbance data,and Landsat 8 OLI satellite imagery.We assessed different combinations of these datasets using three models,a semiparametric generalized additive model（GAM） and two nonlinear models（sigmoidal and exponential）,employing a genetic algorithm for variable selection that minimized root mean square prediction error（RMSPE）,calculated through cross-validation.We compared model fit statistics to a null model as a baseline estimation method.Using bootstrap resampling methods,we calculated 95% confidence intervals for each model and compared results to a simple estimate of mean AGB from the NFI ground plot data.Results：Canopy cover,soil moisture,and vegetation indices were consistently selected as predictor variables.The sigmoidal model and the GAM performed similarly;for both models the RMSPE was -36.8 tonnes per hectare（i.e.,57% of the mean）.However,the sigmoidal model was approximately 30% more efficient than the GAM,assessed using bootstrapped variance estimates relative to a null model.After selecting the sigmoidal model,we estimated total AGB for the study area at 64,526,209 tonnes（＋/- 477,730）,with a confidence interval 20 times more precise than a simple designbased estimate.Conclusions：Our findings demonstrate that NFI data may be combined with freely available satellite imagery and soils data to estimate total AGB with quantifiable uncertainty,while also providing spatially explicit AGB maps useful for management,planning,and reporting purposes.

Plant cover as an estimator of above-ground biomass in semi-arid woody vegetation in Northeast Patagonia,Argentina

The quantification of carbon storage in vegetation biomass is a crucial factor in the estimation and mitigation of CO2 emissions.Globally,arid and semi-arid regions are considered an important carbon sink.However,they have received limited attention and,therefore,it should be a priority to develop tools to quantify biomass at the local and regional scales.Individual plant variables,such as stem diameter and crown area,were reported to be good predictors of individual plant weight.Stand-level variables,such as plant cover and mean height,are also easy-to-measure estimators of above-ground biomass(AGB)in dry regions.In this study,we estimated the AGB in semi-arid woody vegetation in Northeast Patagonia,Argentina.We evaluated whether the AGB at the stand level can be estimated based on plant cover and to what extent the estimation accuracy can be improved by the inclusion of other field-measured structure variables.We also evaluated whether remote sensing technologies can be used to reliably estimate and map the regional mean biomass.For this purpose,we analyzed the relationships between field-measured woody vegetation structure variables and AGB as well as LANDSAT TM-derived variables.We obtained a model-based ratio estimate of regional mean AGB and its standard error.Total plant cover allowed us to obtain a reliable estimation of local AGB,and no better fit was attained by the inclusion of other structure variables.The stand-level plant cover ranged between 18.7%and 95.2%and AGB between about 2.0 and 70.8 Mg/hm^(2).AGB based on total plant cover was well estimated from LANDSAT TM bands 2 and 3,which facilitated a model-based ratio estimate of the regional mean AGB(approximately 12.0 Mg/hm^(2))and its sampling error(about 30.0%).The mean AGB of woody vegetation can greatly contribute to carbon storage in semi-arid lands.Thus,plant cover estimation by remote sensing images could be used to obtain regional estimates and map biomass,as well as to assess and monitor the impact of land-use change on the carbon balance,for arid and semi-arid regions.

Assessment of tree diversity and above-ground biomass in coffee agroforest dominated tropical landscape of India's Central Western Ghats

The purpose of this study was to quantify the changes in tree diversity and above-ground biomass associated with six land-use types in Kodagu district of India's Western Ghats. We collected data on species richness,composition and above-ground biomass(AGB) of trees,shrubs and herbs from 96 sample plots of 0.1 ha. Totals of83 species from 26 families were recorded across the landuses. Tree species richness, diversity and composition were significantly higher in evergreen forest(EGF) than in other land-uses. Similarly, stem density and basal area were greater in EGF compared to other land-uses. Detrended correspondence analysis(DCA) yielded three distinct groups along the land-use intensities and rainfall gradient on the first and second axes, respectively. The first DCA axis accounted for 45% and second axis for 35% of the total variation in species composition. Together the first two axes accounted for over 2/3 of the variation in species composition across land-use types. Across the land-uses,AGB ranged from 58.6 Mg ha-1 in rubber plantation to327.3 Mg ha-1 in evergreen forest. Our results showed that species diversity and AGB were negatively impacted bythe land-use changes. We found that coffee agroforests resembled natural forest and mixed species plantation in terms of tree diversity and biomass production, suggesting that traditional coffee farms can help to protect tree species, sustain smallholder production and offer opportunities for conservation of biodiversity and climate change mitigation.

Land use and above-ground biomass changes in a mountain ecosystem,northern Thailand

The conversion of forests into agricultural lands is a major cause of deforestation,particularly in the mountain ecosystems of northern Thailand.It results in a rapid loss of biological diversity of both flora and fauna.In addition,the above-ground biomass(AGB),which can be a major source of carbon storage,is also decreased.This study aimed to predict the AGB in Doi Suthep-Pui National Park,Chiang Mai province,based on land-use/land cover(LULC)changes from 2000 to 2030.Landsat-5 TM(2000)and Landsat-8 TM(2015)satellite images were analyzed to predict LULC changes to 2030.Temporary plots(30 m 930 m)were established in each LULC type for AGB analysis;trees with diameters at breast height≥4.5 cm were identified and measured.AGB of all LULC types were analyzed based on specific allometric equations of each type.The results show that area of forest and nonforested areas fluctuated during the study period.Through the first 15 years(2000–2015),5%(2.9 km^2)of forest changed to either agriculture or urban lands,especially mixed deciduous forest and lower montane forest.There was a similar trend in the 2030 prediction,showing the effect of forest fragmentation and the resultant high number of patches.Total AGB tended to decrease over the 30-year period from 12.5 to 10.6 t ha^-1 in the first and second periods,respectively.Deforestation was the main factor influencing the loss of AGB(30.6 t ha^-1)related to LULC changes.Furthermore,habitat loss would be expected to result in decreased biological diversity.Consequently,a management plan should be developed to avoid unsustainable land use changes,which may adversely affect human well-being.

Tree Allometry in Tropical Forest of Congo for Carbon Stocks Estimation in Above-Ground Biomass

The research was aimed to estimate the carbon stocks of above-ground biomass (AGB) in Lesiolouna forest in Republic of Congo. The methodology of Allometric equations was used to measure the carbon stock of Lesio-louna tropical rainforest. The research was done with six circular plots each 40 m of diameter, with a distance of 100 m between each plot, depending on the topography of the site of the installation of these plots. The six studied plots are divided in two sites, which are: Iboubikro and Ngambali. Thus, in the six plots, there are three plots in Iboubikro site and three plots in Ngambali site. The results of this study show that the average carbon stock of aboveground biomass (AGB) in six plots was 170.673 t C ha-1. So, the average of carbon stock of aboveground biomass (ABG) in Iboubikro site was 204.693 t C ha-1 and in the Ngambali site was 136.652 t C ha-1. In this forest ecosystem, the high stock of carbon was obtained in Plot 3, which was in Iboubikro site. Plot 3 contains 20 trees and an average DBH of 24.56 cm. However, the lowest carbon stock was obtained in Plot 4, which was in Ngambali site. Also, Plot 4 contains 11 trees and an average DBH of 31.86 cm. The results of this research indicate that, the forests in the study area are an important carbon reservoir, and they can also play a key role in mitigation of climate change.

Prospects and Problems of Implementation of Recreation Works in Degradated Areas

This article is devoted to work aimed at normalizing the condition of degraded soils in open-pit mines as a result of anthropogenic influences through phytomass. By creating a biological cover from plants, it has been achieved to improve the composition of the soil. Plants such as Datura starmonium, Portuluca oleracea, Caspella bursa-pastoris, Chenopodium vulvaria, Chenopodium album, Plantago lanceolata, Vaccaria hispanica, Vicia angustifolia were used for the research. The effect of micronutrients on plants was studied.

Biomass Prediction Equation for Colophospermum mopane (Mopane) in Botswana

This study aimed to develop a biomass equation for estimating the total above-ground biomass for Colophospermum mopane (mopane) based on the pooled data from three study sites. The mopane woodlands in Botswana represent 14.6% of Botswana’s total area. The woodlands directly or indirectly support the livelihood of the majority of the rural population by providing wood and non-wood products. However, there is limited information on the pattern, trends and distribution of woody biomass production and their primary, environmental, and climatic determinants in different parts of Botswana. All the data were collected by destructive sampling from three study sites in Botswana. Stratified random sampling was based on the stem diameter at breast height (1.3 m from the ground or Diameter at Breast Height (DBH)). A total of 30 sample trees at each study site were measured, felled and weighed. The data from the three sites were pooled together, and the study employed regression analysis to examine the nature of relationships between total above-ground biomass (dependent variable) and five independent variables: 1) total tree height;2) crown diameter;3) stem diameters at 0.15 m;1.3 m (DBH) and 3 m from the ground respectively. There were significant relationships between all the independent variables and the dependent variable. However, DBH emerged as the strongest predictor of total tree above-ground biomass for mopane. The equation lnBiomass=-1.163+2.190lnDBH was adopted for use in the indirect estimation of total tree above-ground biomass for mopane in Botswana.

金露梅灌丛净第一性生产力

甘肃天祝金强河地区金露梅灌丛的植物种类组成随海拔和地形的不同有所差异 ,构成金露梅群落的植物生活型以地面芽 ( 4 6.35% )和地下芽 ( 2 7.94 % )植物为主 ,矮高位芽 ( 14.0 2 % )和一年生植物 ( 11.6% )次之。群落的地上植物量在生长季呈单峰曲线变化 ,放牧较重的灌丛群落植物量峰值较未放牧或较轻放牧的提前 1个月出现 ,正常情况下群落、灌木、草本的地上植物量峰值一般出现于 8月 ;群落地上净第一性生产力和对总辐射的转化率分别为 2 52 .0 4 g/ (m2 ·a)和0 .0 77%。

播期对浑善达克沙地青贮玉米产量及生物量分配的影响

为研究播期对浑善达克沙地青贮玉米产量和生物量分配的影响,确定当地青贮玉米最佳的播期,分别在5月27日、6月4日、6月11日和6月18日4个时间播种,测定了不同品种青贮玉米的株高、叶面积及地上生物量。8月27日青贮收获结果显示:随播期推迟,青贮玉米株高、叶面积和地上生物量降低;5月27日和6月4日播种的青贮玉米各指标均显著高于6月11日和6月18日播种的青贮玉米(P<0.05)。说明将当前生产实践中播种时间由6月中旬提前至5月底和6月初可显著提高青贮玉米产量。生物量分配研究表明,随播期推迟收获时茎生物量所占比例下降,叶生物量所占比例升高。由于玉米茎、叶的饲用性和牲畜利用效率不同,可针对不同饲喂需求选择播种时间,以提高青贮玉米的利用率。

灌溉与草坪草地下植物量关系的研究

采用大田试验和室内分析相结合的方法,探讨了不同灌溉量与草坪地下植物量的关系及地下植物量动态变化、根系的空间分布,结果表明,在三种草坪草中,高羊茅抗旱性最强,多年生黑麦草抗旱性最差;地下植物量最大值出现在春季,秋季为根系的恢复生长期;轻度水分胁迫有助于根系的生长,充足水分条件并不利于高羊茅根系生长;根系的空间分布呈乘幂关系。

几种草坪草地上和地下植物量的比较研究

以我国常用的11种(品种)草坪草为对象,对其盖度、地上部茎叶量、总根量进行了观测与比较分析,最后得出:(1)供试草种根系大部分(83.1%～69.07%)集中分布于土壤表层(0～10cm);(2)在盖度、均匀度及对外界干扰的适应能力等方面瓦巴斯、狗牙根和苔草表现尚优;(3)在试验条件下,茎叶量瓦巴斯、狗牙根最高,菲尔金最低。根量与茎叶量比值,结缕草和瓦巴斯最大,菲尔金最低。

分根PEG胁迫对羊草幼苗植物量、活性氧代谢及脯氨酸含量的影响

采用分根装置,在自动控制的遮雨棚中,研究了聚乙二醇(PEG)胁迫对羊草幼苗植物量、活性氧代谢以及脯氨酸含量的影响.结果表明:与对照(CK,1/2强度Hoagland营养液)相比,单一根茎胁迫(RHS)、单一根系胁迫(ROS)以及同时根茎和根系胁迫(RHSS)3种处理方式均显著降低了羊草幼苗地上部干重、根茎干重以及总干重,且ROS处理和RHSS处理的降低幅度较大.RHS处理时,羊草幼苗根系中SOD、CAT活性显著降低,而根茎SOD、CAT活性增加.ROS和RHSS处理下,叶片中SOD、POD和CAT活性均有上升趋势;根茎在ROS处理下SOD、CAT活性均增加,RHSS处理下仅SOD活性上升,而根系在ROS处理下仅CAT活性上升.羊草地上部脯氨酸含量在RHS、ROS和RHSS处理时均显著增加,而根茎则显著降低.可见,根茎和根系在羊草响应PEG胁迫的生理过程中具有不同的功能;PEG胁迫下羊草不同器官同一抗氧化酶对活性氧淬灭作用不同,与POD相比不同器官SOD和CAT作用可能更大.

贺兰山苔藓植物物种多样性、生物量及生态学作用的研究

研究了贺兰山不同海拔高度主要林型种苔藓植物物种多样性、生物量和生态学作用．结果表明：云杉林下藓类地被层的生物量最高，９１４７．７ｋｇ／ｈｍ２，是林下灌木和草本植物总生物量的９．２倍，在饱和吸水状态下，可贮存水２０１７４．５ｋｇ／ｈｍ２．通过随机取样按海拔高度、林型和土壤类型等梯度对贺兰山苔藓植被进行了调查，影响苔藓植物生长和分布的主要生态因子是光照，相对湿度、海拔高度和土壤ｐＨ。

金露梅株丛的植物量及其空间分布的研究

研究了东祁连山金露梅株丛的植物量形成规律，空间分布特点及其与立地类型的关系。结果表明，地上植物量８月底最高，６月生长最快，１０月凋落速度最快。年凋落量是年增量的７２％左右。株丛植物量Y与株丛分枝数Ｘ１、丛高Ｘ２、株丛投影面积Ｘ３成正相关关系，可用多元线性回归方程Ｙ干质量＝－３２５.３４６十１０．４２１Ｘ2＋０.１１０Ｘ３（ｒ＝０.８５７，Ｐ＜０.０１）或Ｙ鲜质量＝２１０.６３７＋７.２１８Ｘ1＋１.４００Ｘ２＋０．０８７Ｘ３（ｒ＝０．８７２．Ｐ＜０．０１）来估测，估测精度分别为９１．２％和９５.８％。地上植物量的８０％分布于０～３０ｃｍ高度内，地下植物量的８５％集中分布于０～２０ｃｍ的土层中。株丛地下植物量３７８．９ｇ／ｍ２·ＤＭ是地上植物量３２６.６ｇ／ｍ２ＤＭ的１．２倍，地下部分所占空间是地上的３５～１０.２倍。不同立地条件下金露梅株丛的分枝数不同，单枝质量差异很大。