Improving the Accuracy of Vegetation Index Retrieval for Biomass by Combining Ground-UAV Hyperspectral Data-A New Method for Inner Mongolia Typical Grasslands

Grassland biomass is an important parameter of grassland ecosystems.The complexity of the grassland canopy vegetation spectrum makes the long-term assessment of grassland growth a challenge.Few studies have explored the original spectral information of typical grasslands in Inner Mongolia and examined the influence of spectral information on aboveground biomass(AGB)estimation.In order to improve the accuracy of vegetation index inversion of grassland AGB,this study combined ground and Unmanned Aerial Vehicle(UAV)remote sensing technology and screened sensitive bands through ground hyperspectral data transformation and correlation analysis.The narrow band vegetation indices were calculated,and ground and airborne hyperspectral inversion models were established.Finally,the accuracy of the model was verified.The results showed that:(1)The vegetation indices constructed based on the ASD FieldSpec 4 and the UAV were significantly correlated with the dry and fresh weight of AGB.(2)The comparison between measured R^(2) with the prediction R^(2) indicated that the accuracy of the model was the best when using the Soil-Adjusted Vegetation Index(SAVI)as the independent variable in the analysis of AGB(fresh weight/dry weight)and four narrow-band vegetation indices.The SAVI vegetation index showed better applicability for biomass monitoring in typical grassland areas of Inner Mongolia.(3)The obtained ground and airborne hyperspectral data with the optimal vegetation index suggested that the dry weight of AGB has the best fitting effect with airborne hyperspectral data,where y=17.962e^(4.672x),the fitting R^(2) was 0.542,the prediction R^(2)was 0.424,and RMSE and REE were 57.03 and 0.65,respectively.Therefore,established vegetation indices by screening sensitive bands through hyperspectral feature analysis can significantly improve the inversion accuracy of typical grassland biomass in Inner Mongolia.Compared with ground monitoring,airborne hyperspectral monitoring better reflects the inversion of actual surface biomass.It provides a reliable modeling framework for grassland AGB monitoring and scientific and technological support for grazing management.

Biomass Components and Environmental Controls in Ningxia Grasslands

Grassland plays an important role in the global carbon cycle and climate regulation. However, there are still large uncertainties in grassland carbon pool and also its role in global carbon cycle due to the lack of measured grassland biomass at regional scale or global scale with a unified survey method, particular for below-ground biomass. The present study, based on a total of 44 grassland sampling plots with 220 quadrats across Ningxia, investigated the characteristics of above-ground biomass （AGB）, below-ground biomass （BGB）, litter biomass （LB）, total biomass （TB） and root：shoot ratios （R：S） for six predominantly grassland types, and their relationships with climatic factors. AGB, BGB, LB and TB varied markedly across different grassland types, the median value ranging from 28.2-692.6 g m-2 for AGB, 130.4-2 036.6 g m-： for BGB, 9.2-82.3 g m2 for LB, and 168.0-2 681.3 g m-： for TB. R：S showed less variation with median values from 3.2 to 5.3 （excluding marshy meadow）. The different grassland types showed similar patterns of biomass allocation, with more than 70% BGB for all types. There is evidence of strong positive effects associated with mean annual precipitation （MAP） and negative effects associated with mean annual temperature （MAT） on AGB, BGB, and LB, although both factors have the opposite effect on R：S.

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.

Dynamic of Grassland Biomass in Different Degenerative Stages

The dynamics of plant community and above- and belowground biomass of the different degenerative stages was researched of Kobresia hurnlis meadows of Nakchu prefecture in Tibet Autonomous Region. The results indicated that the aggravation of the degree of deterioration of alpine meadow is, the lower the vegetation coverage, percentage of excellent forage, and biodiversity are. The total aboveground biomass is highest in the lightly degraded stages while it is lowest in the extremely degraded stages. With the aggravation of degradation, the aboveground biomass of forbs increases while that of Cyperaceae decreases. We found that the belowground biomass was mostly distributed in the 0-10 cm soil depth in the alpine meadow with a ＂T＂-shape distribution feature, and with the acceleration of deterioration, the numbers of roots becomes less and less. Meanwhile, the above- and belowground biomass of the different degraded communities was significantly correlated（r= 0. 963）. There is an obvious positive correlation with the above- and belowground biomass in different degenerative stages, and their ratio increased with the aggravation of degradation.

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.

Ecological stoichiometry and biomass response of Agropyron michnoi Roshev.under simulated N deposition in a sandy grassland,China

Sandy grassland in northern China is a fragile ecosystem with poor soil fertility.Exploring how plant species regulate growth and nutrient absorption under the background of nitrogen(N)deposition is crucial for the management of the sandy grassland ecosystem.We carried out a field experiment with six N levels in the Hulunbuir Sandy Land of China from 2014 to 2016 and explored the Agropyron michnoi Roshev.responses of both aboveground and belowground biomasses and carbon(C),N and phosphorus(P)concentrations in the plant tissues and soil.With increasing N addition,both aboveground and belowground biomasses and C,N and P concentrations in the plant tissues increased and exhibited a single-peak curve.C:N and C:P ratios of the plant tissues first decreased but then increased,while the trend for N:P ratio was opposite.The peak values of aboveground biomass,belowground biomass and C concentration in the plant tissues occurred at the level of 20 g N/(m2•a),while those of N and P concentrations in the plant tissues occurred at the level of 15 g N/(m2•a).The maximum growth percentages of aboveground and belowground biomasses were 324.2%and 75.9%,respectively,and the root to shoot ratio(RSR)decreased with the addition of N.N and P concentrations in the plant tissues were ranked in the order of leaves>roots>stems,while C concentration was ranked as roots>leaves>stems.The increase in N concentration in the plant tissues was the largest(from 34%to 162%),followed by the increase in P(from 10%to 33%)and C(from 8%to 24%)concentrations.The aboveground biomass was positively and linearly correlated with leaf C,N and P,and soil C and N concentrations,while the belowground biomass was positively and linearly correlated with leaf N and soil C concentrations.These results showed that the accumulation of N and P in the leaves caused the increase in the aboveground biomass,while the accumulation of leaf N resulted in the increase in the belowground biomass.N deposition can alter the allocation of C,N and P stoichiometry in the plant tissues and has a high potential for increasing plant biomass,which is conducive to the restoration of sandy grassland.

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.

Estimation of the Above-ground Biomass of Tamarix Species along a Transect at the Tarim River's Middle Reaches

[Objective] The purpose was to research the distribution characteristics of Tamarix species above-ground biomass of Tarim River＇s middle reaches and to find out best-fit linear-regression model of Tamarix species in this area.[Method] By dint of the most common sampling method PCQ,five samples in the middle reaches of Tarim River were collected.The best-fit linear-regression model of Tamarix species of this area was set up,based on the fieldwork and the model of Evangelista and obtained the distribution rules of Tamarix species of Tarim River＇s middle reaches.[Result] The result indicated that this model fitted for the estimation of aboveground biomass of the study area.According to the distribution rules of aboveground biomass,it was clear that underground water was the major element which decided the distribution of aboveground biomass.[Conclusion] The study provided theoretical basis for the calculation of biomass of Tamarix.

Remote Sensing-based Spatiotemporal Distribution of Grassland Aboveground Biomass and Its Response to Climate Change in the Hindu Kush Himalayan Region

The grassland in the Hindu Kush Himalayan(HKH) region is one of the large st and most biodiverse mountain grassland types in the world,and its ecosystem service functions have profound impacts on the sustainable development of the HKH region.Monitoring the spatiotemporal distribution of grassland aboveground biomass(AGB) accurately and quantifying its response to climate change are indispensable sources of information for sustainably managing grassland ecosystems in the HKH region.In this study,a pure vegetation index model(PVIM) was applied to estimate the long-term dynamics of grassland AGB in the HKH region during 2000-2018.We further quantified the response of grassland AGB to climate change(temperature and precipitation) by partial correlation and variance partitioning analyses and then compared their differences with elevation.Our results demonstrated that the grassland AGB predicted by the PVIM had a good linear relationship with the ground sampling data.The grassland AGB distribution pattern showed a decreasing trend from east to west across the HKH region except in the southern Himalayas.From 2000 to 2018,the mean AGB of the HKH region increased at a rate of 1.57 g/(m~2·yr) and ranged from 252.9(2000) to 307.8 g/m~2(2018).AGB had a positive correlation with precipitation in more than 80% of the grassland,and temperature was positively correlated with AGB in approximately half of the region.The change in grassland AGB was more responsive to the cumulative effect of annual precipitation,while it was more sensitive to the change in temperature in the growing season;in addition,the influence of climate varied at different elevations.Moreover,compared with that of temperature,the contribution of precipitation to grassland AGB change was greater in approximately 60% of the grassland,but the differences in the contribution for each climate factor were small between the two temporal scales at elevations over 2000 m.An accurate assessment of the temporal and spatial distributions of grassland AGB and the quantification of its response to climate change are of great significance for grassland management and sustainable development in the HKH region.

Effects of spring fire and slope on the aboveground biomass, and organic C and N dynamics in a semi-arid grassland of northern China

The aboveground primary production is a major source of carbon(C) and nitrogen(N) pool and plays an important role in regulating the response of ecosystem and nutrient cycling to natural and anthropogenic disturbances. To explore the mechanisms underlying the effect of spring fire and topography on the aboveground biomass(AGB) and the soil C and N pool, we conducted a field experiment between April 2014 and August 2016 in a semi-arid grassland of northern China to examine the effects of slope and spring fire, and their potential interactions on the AGB and organic C and total N contents in different plant functional groups(C_3 grasses, C_4 grasses, forbs, Artemisia frigida plants, total grasses and total plants).The dynamics of AGB and the contents of organic C and N in the plants were examined in the burned and unburned plots on different slope positions(upper and lower). There were differences in the total AGB of all plants between the two slope positions. The AGB of grasses was higher on the lower slope than on the upper slope in July. On the lower slope, spring fire marginally or significantly increased the AGB of C_3 grasses, forbs, total grasses and total plants in June and August, but decreased the AGB of C_4 grasses and A.frigida plants from June to August. On the upper slope, however, spring fire significantly increased the AGB of forbs in June, the AGB of C_3 grasses and total grasses in July, and the AGB of forbs and C_4 grasses in August. Spring fire exhibited no significant effect on the total AGB of all plants on the lower and upper slopes in 2014 and 2015. In 2016, the total AGB in the burned plots showed a decreasing trend after fire burning compared with the unburned plots. The different plant functional groups had different responses to slope positions in terms of organic C and N contents in the plants. The lower and upper slopes differed with respect to the organic C and N contents of C_3 grasses, C_4 grasses, total grasses, forbs, A. frigida plants and total plants in different growing months. Slope position and spring fire significantly interacted to affect the AGB and organic C and N contents of C_4 grasses and A. frigida plants. We observed the AGB and organic C and N contents in the plants in a temporal synchronized pattern. Spring fire affected the functional AGB on different slope positions, likely by altering the organic C and N contents and, therefore,it is an important process for C and N cycling in the semi-arid natural grasslands. The findings of this study would facilitate the simulation of ecosystem C and N cycling in the semi-arid grasslands in northern China.

Effects of freezing intensity on soil solution nitrogen and microbial biomass nitrogen in an alpine grassland ecosystem on the Tibetan Plateau,China

The change of freeze-thaw pattern of the Tibetan Plateau under climate warming is bound to have a profound impact on the soil process of alpine grassland ecosystem;however,the research on the impact of the freeze-thaw action on nitrogen processes of the alpine grassland ecosystem on the Tibetan Plateau has not yet attracted much attention.In this study,the impact of the freezing strength on the soil nitrogen components of alpine grassland on the Tibetan Plateau was studied through laboratory freeze-thaw simulation experiments.The 0–10 cm topsoil was collected from the alpine marsh meadow and alpine meadow in the permafrost region of Beilu River.In the experiment,the soil samples were cultivated at –10℃,–7℃,–5℃,–3℃ and –1℃,respectively for three days and then thawed at 2℃ for one day.The results showed that after the freeze-thaw process,the soil microbial biomass nitrogen significantly decreased while the dissolved organic nitrogen and inorganic nitrogen significantly increased.When the freezing temperature was below –7℃,there was no significant difference between the content of nitrogen components,which implied a change of each nitrogen component might have a response threshold toward the freezing temperature.As the freeze-thaw process can lead to the risk of nitrogen loss in the alpine grassland ecosystem,more attention should be paid to the response of the soil nitrogen cycle of alpine grasslands on the Tibetan Plateau to the freeze-thaw process.

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.

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.

Changes in the relationship between species richness and belowground biomass among grassland types and along environmental gradients in Xinjiang, Northwest China

The association between biodiversity and belowground biomass(BGB) remains a central debate in ecology.In this study, we compared the variations in species richness(SR) and BGB as well as their interaction in the top(0–20 cm), middle(20–50 cm) and deep(50–100 cm) soil depths among 8 grassland types(lowland meadow, temperate desert, temperate desert steppe, temperate steppe desert, temperate steppe, temperate meadow steppe, mountain meadow and alpine steppe) and along environmental gradients(elevation, energy condition(annual mean temperature(AMT) and potential evapotranspiration(PET)), and mean annual precipitation(MAP)) based on a 2011–2013 survey of 379 sites in Xinjiang, Northwest China.The SR and BGB varied among the grassland types.The alpine steppe had a medium level of SR but the highest BGB in the top soil depth, whereas the lowland meadow had the lowest SR but the highest BGB in the middle and deep soil depths.The SR and BGB in the different soil depths were tightly associated with elevation, MAP and energy condition;however, the particular forms of trends in SR and BGB depended on environmental factors and soil depths.The relationship between SR and BGB was unimodal in the top soil depth, but SR was positively related with BGB in the middle soil depth.Although elevation, MAP, energy condition and SR had significant effects on BGB, the variations in BGB in the top soil depth were mostly determined by elevation, and those in the middle and deep soil depths were mainly affected by energy condition.These findings highlight the importance of environmental factors in the regulations of SR and BGB as well as their interaction in the grasslands in Xinjiang.

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.

Biomass of Natural Grassland under Different Enclosure Conditions

Taking natural grassland on the northern slope of the Qilian Mountain for example, this paper investigated and compared aboveground and belowground biomass of grassland in multi-year enclosure(20 years), one-year enclosure, control areas(natural grazing areas). The results showed that coverage and height of the enclosure sample plots were significantly higher than that of natural grazing area(P <0.05); mean aboveground biomass of grassland: multi-year enclosure(316.58 g/m^2) > one-year enclosure area(299.07 g/m^2) > multi-year enclosure control area(254.39 g/m^2) > one-year enclosure control area(187.37 g/m^2); belowground biomass: multi-year enclosure(2,906.90 g/m^2) > one-year enclosure area(2,587.26 g/m^2) > multi-year enclosure control area(2,378.93 g/m^2) > one-year enclosure control area(2,029.17 g/m^2); mean aboveground biomass of natural grassland was 263.60 g/m^2, mean belowground biomass 2,225.56 g/m^2; ratio of belowground biomass to aboveground biomass varied between 6.79 and 12.90, distribution of belowground biomass and aboveground biomass in each plot showed significant differences(P <0.05). Enclosure was favorable for improving the coverage and biomass of natural grassland plant communities in the Qilian Mountains.

Allometric prediction of above-ground biomass of eleven woody tree species in the Sudanian savanna-woodland of West Africa

Allometric models are necessary for estimating biomass in terrestrial ecosystems. Generalized allometric relationship exists for many tropical trees, but species- and region-specific models are often lacking. We developed species-specific allometric models to predict aboveground biomass for 11 native tree species of the Sudanian savanna- woodlands. Diameters at the base and at breast height, with species means ranging respectively from 11 to 28 cm and 9 to 19 cm, and the height of the trees were used as predictor variables. Sampled trees spanned a wide range of sizes including the largest sizes these species can reach. As a response variable, the biomass of the trees was obtained through destructive sampling of 4 754 trees during wood harvesting. We used a stepwise multiple regression analysis with backward elimination procedure to develop models separately predicting, total biomass of the trees, stem biomass, and biomass of branches and twigs. All species- specific regression models relating biomass with measured tree dimen- sions were highly significant （p 〈 0.001）. The biomass of branches and twigs was less predictable compared to stem biomass and total biomass, although their models required fewer predictors and predictor interac- tions. The best-fit equations for total above-ground biomass and stem biomass bad R2 〉 0.70, except for the Acacia species; for branches including twig biomass, R2-values varied from 0.749 for Anogeissus leiocarpa to 0.183 for Acacia macrostachya. The use of these equations in estimating available biomass will avoid destructive sampling, and aid in planning for sustainable use of these species.

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.

Response of Grassland Biomass to Soil Moisture in the Arid Mountainous Area of the Qilian Mountains

The Pailugou watershed of the Qilian Mountains in the arid region of northeast China was selected for research to analyze the species, height, and biomass in typical mountain grassland with an altitude of 2,700–3,000 m and measure soil moisture, so as to explore the seasonal characteristics of grassland biomass as altitude increases and the relationship between grassland biomass and soil moisture. The results showed that:(1) with a mean value of 135.36 g/m^2, grassland aboveground biomass showed a unimodal distribution from rise to decline as altitude increased, and reached its maximum of 176.79 ± 28.37 g/m^2 at an altitude of 2,900 m; with a mean value of 946.13 g/m^2, grassland underground biomass showed an uptrend as altitude increased, and reached its maximum of 1,301.19 ± 68.24 g/m^2 at an altitude of 3,000 m;(2) the difference between aboveground biomass and underground biomass in the grassland at different altitudes was significant;(3) values of root shoot ratio of the arid mountain grassland varied between 4.14–11.95;(4) values of soil moisture content of the arid mountain grassland varied between 9.23%–31.31%;(5) there was a positive correlation between aboveground biomass and underground biomass and the mean soil moisture content(p < 0.05), with a correlation coefficient of 0.778 4 and 0.784 3 respectively, soil layers with different moisture content made different contributions to grassland biomass, and moisture content in the soil layer where over-60-cm root systems were located was of significance to grassland biomass.

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.