Distribution Of Stocks Research Articles

喀斯特地区碳储量对土地利用模式的响应——以南北盘江流域为例

PDF HTML阅读 XML下载 导出引用 引用提醒 喀斯特地区碳储量对土地利用模式的响应——以南北盘江流域为例 DOI: 10.5846/stxb202208192384 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 贵州省基础研究(自然科学)项目(黔科合基础-ZK[2022]一般 302);贵州省基础研究(自然科学)项目(黔科合基础[20201Y154]);国家自然科学基金(41661088);贵州省自然资源厅项目-贵州省不动产经济运行评审体系建设项目(HXDZB-022) Responses of carbon storage to land use pattern in karst area: A case study of Nanbei Panjiang River Basin Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:喀斯特地区生态系统脆弱,对气候变化响应敏感,空间异质性强,碳汇潜力大。喀斯特生态治理对土地利用格局的改变,会导致生态系统碳储量的显著变化,对陆地生态系统碳循环和区域生态安全具有深远影响。以喀斯特典型区南北盘江流域为例,运用InVEST模型和热点分析评估流域2000-2020年土地利用变化对碳储量时空分布的影响,根据碳储量集聚特征使用FLUS-Markov模型分区预测生态系统碳储量对不同土地利用模式的响应。结果表明:(1)2000-2020年,研究区土地利用类型由高碳密度的地类转为较低碳密度的地类,致使生态系统碳储量呈减少趋势,累计损失90.36×105t C。(2)2000-2020年碳储量在空间上呈现"西低东高"的格局。热点区集中分布在东部和东南部,冷点区主要分布在西部和西南部,弱显著区大多在北部。(3)各热点分区在不同模式下固碳能力差异显著。热点区在不同模式下的平均碳密度均大于155.40t/hm2,显著高于2020年南北盘江流域的平均碳密度143.59t/hm2,整体固碳功能突出;弱显著区的碳汇能力与研究区平均水平相近,自然发展模式(NDP)和经济建设模式(ECP)下碳储量损失较少;冷点区在NDP、ECP下碳储量损失剧烈,但在生态保护模式(EPP)下碳汇增加速率为1.38×105t/a,明显高于弱显著区(0.30×105t/a),碳汇潜力较大。总体上,EPP影响下的土地利用格局固碳能力优于NDP和ECP。该研究可为喀斯特地区土地利用格局优化和生态系统管理提供科学依据。 Abstract:As we all know, karst areas have fragile ecosystems with strongly spatial heterogeneity and large carbon sink potential, which is sensitive to climate change. The change of land use pattern caused by karst ecological governance will lead to significant changes in ecosystem carbon storage, which has far-reaching impacts on the carbon cycle of the terrestrial ecosystem and regional ecological security. Take the Nanbei Panjiang River Basin in the typical karst area as an example, the InVEST model and hotspot analysis were used to assess the impacts of land use change on the spatial and temporal distribution of carbon stocks in the Nanbei Panjiang River Basin from 2000 to 2020. At the same time, the FLUS-Markov model was used to predict the changes of ecosystem carbon storages under different land use patterns, according to the characteristics of carbon storage agglomeration. Research results showed that: (1) from 2000 to 2020, the land use type in the study area has changed from high carbon density to low carbon density, resulting in a cumulative loss of 90.36×105 t in ecosystem carbon storage. (2) Carbon storage presented a spatial pattern of "low in west and high in east" area. Hot spots were concentrated in the east and southeast study area, while cold spots were mainly distributed in the west and southwest and weak significant areas were mostly in the north area. (3) Under different patterns, the carbon fixation capacities of each hot spots were significantly different. The average carbon density of hot spots was more than 155.40 t/hm2, which was obviously higher than the average carbon density of Nanbei Panjiang River Basin (143.59 t/hm2) in 2020. At the same time, the carbon sink capacity of the weakly significant area was close to the average level of the study area, and the carbon storage loss was less under Natural Development Pattern (NDP) and Economic Development Pattern (ECP). On the one hand, the carbon storage loss was severe in cold spot area under NDP and ECP, on the other hand the carbon sink increase rate was 1.38×105 t/a under Ecological Protection Pattern (EPP), which was significantly higher than the weakly significant area (0.30×105 t/a). In general, it means that the carbon fixation capacity of land use pattern under the influence of EPP is better than that of NDP and ECP. This study can provide some scientific basis for the optimization of land use pattern and ecosystem management in karst areas. 参考文献 相似文献 引证文献

Estimation of aboveground carbon stock using the 8 operation land imagery in Lemo Nakai community forest, Indonesia

Estimation of aboveground carbon stock on stands vegetation, especially in community forests in Indonesia has become an urgent issue in the effort to calculate, monitor, manage, and evaluate carbon stocks. The study aims to test the accuracy of the estimated model of aboveground carbon stocks, to ascertain the total carbon stock, and to map the spatial distribution of carbon stocks on stands vegetation in Lemo Nakai community forest lying on 3°25’59,588” - 3 27’57,982” alt. and 102°19’25,108” - 102°22’23,416” long., covering 1,053. 53 ha. The study was conducted from February to June 2022 at Baturaja Village, North Bengkulu District. Forest structure grouped classified into three classes; dense, medium and sparse stand using stratified sampling plots systematically spread out at the forest studied forest area. Above-ground biomass and carbon stock of the forest stand were estimated using allometric models. Spatial data collected from Landsat 8 OLI (operational land imager) were used to produce land-use maps of the Lemo Nakai community forest to estimate the total carbon stock, obtained from the United State Geological Survey (USGS, 2021). The result showed that the dense-, medium-, and sparse forest structure covered about 753,69 ha, 3232,41ha, and 32,49 ha, respectively. Above-ground biomass of the Lemo Nakai community forest was estimated at the dense-, medium-, and sparse structures were, respectively 389.74 tons ha-1, 278.88 tons ha-1, and 149.28 tons ha-1 with carbon stock at 179.40 tons ha-1, 128.29 tons ha-1, and 68.67 tons ha-1, respectively. Furthermore, estimated CO2eq absorption at the dense-, medium-, and sparse forest structure, respectively 657.80 tons ha-1, 470.58 tons ha-1, and 26.98 tons ha-1.

РЕЗУЛЬТАТЫ ИССЛЕДОВАНИЙ АЗОВСКИХ ПОПУЛЯЦИЙ ОСЕТРОВЫХ РЫБ ПРИ ОСУЩЕСТВЛЕНИИ МОНИТОРИНГА ПРОМЫСЛА СТАВНЫМИ ОРУДИЯМИ ЛОВА У КУБАНСКОГО ПОБЕРЕЖЬЯ

Introduction. After depletion of the Russian sturgeon Acipenser gueldenstaedtii Brandt & Ratzeburg, 1833 and stellate sturgeon Acipenser stellatus Pallas, 1771 stocks at the end of the 20th century, their abundance in the Azov and Black Sea Basin has been maintained through the release of the juveniles obtained by the means of artificial reproduction. Resulting from the strengthening protection of the aquatic living resources and gradually increasing number of the released juveniles, since 2014, as evidenced by the research studies, an increase in the population abundance of these fish species and their biomass is observed in the Azov Sea (from 42 t in 2015 to 998 t in 2022). Unstable state of the sturgeon populations in the coastal waters of the Azov Sea predicated the relevance of this work. Its aim was to investigate the distribution and age–length composition of the populations of the sturgeon fish species in the coastal waters of the Azov Sea. Methods. This study was based on the data on age–length composition collected over the course of the investigation of sturgeon by-catches in stationary pound nets in the coastal waters of the Azov Sea within an administrative unit Primorsko-Akhtarsky District (Yasensk and Achuevo Spits). According to its results, out of all sturgeon species, in the autumn season, the stellate sturgeon prevailed—53 %; the share of Russian sturgeon was 43 %, and for beluga sturgeon, it was 4 %. In summer, the Russian sturgeon share in the catches was 79 %, and for stellate sturgeon, it was 21 %. There have also been recorded some differences of the Russian sturgeon and stellate sturgeon length composition between the early spring and middle autumn, which can result from the fact that the sturgeon individual of greater length leave their wintering sites in the Azov Sea open waters earlier and sooner enter the coastal waters in spring. Conclusions. This study makes it possible to improve the assessment of the stock status and distribution for the sturgeon fish species in the Azov Sea.

Feasibility assessment of net zero-energy transformation of building stock using integrated synthetic population, building stock, and power distribution network framework

The transformation to net zero-energy (nZE) building stocks involves harvesting of renewable energy, enhancement of building energy efficiency, incorporation of various supply-side options, and advanced energy management. Although several studies have evaluated the feasibility of nZE for residential areas in cold regions, only a few studies have been conducted on dense urban regions in noncold climate. Additionally, the accommodation of such building stock transformation by the current power distribution network has not been clarified to date. Thus, this study proposes a novel framework integrating synthetic population, activity, building stock, and power distribution network to explore transformation pathways. This was further demonstrated by a case study on a densely populated region covering four cities in Tokyo, Japan. The results signified that complete dissemination of popular energy efficiency measures can reduce the energy demand by 40%. With the reduction in energy demand, nearly nZE condition can be realized only if the building roof area is completely covered by photovoltaics. In particular, one half of the generation would be utilized locally, whereas the remaining would be exported. Moreover, the power distribution network can accommodate the transformation with a slight increase in power distribution loss up to 1% and a modest reinforcement requirement owing to line overloading. Conclusively, this study revealed that the transformation and reinforcement requirement are significantly distinct from those required in cold regions.

The Utilization Premium

We study the interaction of flexible capital utilization and depreciation for expected returns and investment of firms. Empirically, an investment strategy that buys (sells) equities with low (high) utilization rates earns 5% per annum. Utilization predicts excess returns beyond other production-based variables. We reconcile this novel utilization premium quantitatively using a production model. The model suggests that flexible utilization is important for matching the cross-sectional distribution of investment and stock prices jointly. A model without flexible utilization yields many counterfactuals that flexible utilization addresses by making depreciation fluctuate endogenously. Overall, utilization tightens the link between firms’ production and valuations. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4647 .

Distribution of Carbon Stocks in Peat Bottom Based on Thickness Class in Pelalawan Village (Riau Province, Indonesia)

As is well known, tropical peatlands are deposits of terrestrial organic carbon of global importance. It is estimated that around 15% of carbon is stored in peatlands worldwide. Indonesia contains approximately 50% of the world’s tropical peatlands with frequently cited estimates of about 21 Mha. Pelalawan district area (Riau Province) is dominated by peat soils. The land in Pelalawan is mainly covered by industrial plantations of acacia forests and oil palms. The area is very susceptible to the loss of carbon stocks in peat soils due to the opening of drainage channels. This study aims to calculate the carbon stocks of subsurface peatlands in Pelalawan, especially in the research location. The method used is a grid survey, the distance between the particular points is 500 m, which covers the total area of the research site, i.e. 2,500 ha. The number of observation points is 121, which includes measuring the thickness of the peat layer, calculating bulk density, and C organic content. The paper analysed the distribution of carbon stocks in the peat bottom based on the thickness class. The results showed that carbon stocks in the peat bottom in Pelalawan were 218,753.95 tons/ha consisting of 143,138.40 tons/ha in the peat thickness of >300 cm (very deep peatland), 44,999.10 tons/ha in the peat thickness of 200–300 cm (deep peatland), 21,577.67 tons/ha in the peat thickness of 100–200 cm (medium peatland), 4,780.78 tons/ha in the peat thickness of 50–100 (shallow peatland), and 4,258 tons/ha in the peat thickness of 0–50 (very shallow peatland). The research results of this study cover the information on the availability of carbon storage and carbon conservation.

Spatial dynamic evolution of environmental infrastructure governance in China

<p><big>The implementation of environmental protection strategy necessarily requires mapping the amount of capital stock of environmental infrastructure. Through the Weibull distribution function and hyperbolic age-decreasing efficiency model, the provincial environmental infrastructure capital stock in China from 1980 to 2018 is measured cautiously, and its spatial dynamics with the generated pollutants is analyzed using the center of gravity method. It is found that: the spatial distribution of environmental infrastructure capital stock is uneven, and the unevenness in the east-west direction is greater than that in the north-south direction, but the unevenness in the east-west direction is narrowing while the north-south direction is widening; the spatial and temporal distribution of environmental infrastructure capital and environmental pollution vary greatly, and the spatial management of environmental pollution is less accurate.</big></p>

Utilization of Sentinel-2 Imagery in Mapping the Distribution and Estimation of Mangroves' Carbon Stocks in Bengkulu City

The mangroves' aboveground biomass significantly contributes to the global carbon cycle or economic and ecological values. This makes knowledge about the spatial extent of the mangroves indispensable for policymakers. The sequence of mangroves’ condition range also requires remote sensing data to update the geographical information and synthesize carbon stock in Bengkulu. Therefore, this study aims to create a spatial distrribution of mangroves and evaluate their carbon stock in Bengkulu City using Sentinel-2 imagery. The semi-empirical method uses Sentinel-2 imagery through NDVI to appraise and picture the mangroves' aboveground carbon stock. An allometric equation was used to compute the mangroves' aboveground carbon stock from field measurements. Non-linear regression was used to establish a connection between the NDVI calculated from the Sentinel-2 imagery and the mangroves' aboveground biomass measured in the field, which was subsequently used for aboveground carbon estimation. The results showed that mangroves mapping could derive overall accuracy of 89.09%, where the high-density class existed in 135.12 Ha of total area. It was also discovered that Sentinel-2 imagery could estimate mangroves carbon stock up to 61%. The carbon stock estimation based on the imagery has a value of 16.3992 – 115.134 t C/ha, while that of field survey data ranges from 19.69 to 326.06 t C/ha. These results showed that Sentinel-2B spectral data is functional and has a good chance of being able to predict carbon stock.
 
 Keywords : Carbon; mangroves; NDVI; remote sensing; sentinel-2B
 
 Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember
 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

Estimate Forest Aboveground Biomass of Mountain by ICESat-2/ATLAS Data Interacting Cokriging

Compared with the previous full-waveform data, the new generation of ICESat-2/ATLAS (Advanced Terrain Laser Altimeter System) has a larger footprint overlap density and a smaller footprint area. This study used ATLAS data to estimate forest aboveground biomass (AGB) in a high-altitude, ecologically fragile area. The paper used ATLAS data as the main information source and a typical mountainous area in Shangri-La, northwestern Yunnan Province, China, as the study area. Then, we combined biomass data from 54 ground samples to obtain the estimated AGB of 74,873 footprints using a hyperparametric optimized random forest (RF) model. The total AGB was estimated by combining the best variance function model in geostatistics with the slope that is the covariates. The results showed that among the 50 index parameters and three topographic variables extracted based on ATLAS, six variables showed a significant correlation with AGB. They were, in order, number of canopy photons, Landsat percentage canopy, canopy photon rate, slope, number of photons, and apparent surface reflectance. The optimized random forest model was used to estimate the AGB within the footprints. The model accuracy was the coefficient of determination (R2) = 0.93, the root mean square error (RMSE) = 10.13 t/hm2, and the population estimation accuracy was 83.3%. The optimized model has a good estimation effect and can be used for footprint AGB estimation. The spatial structure analysis of the variance function of footprint AGB showed that the spherical model had the largest fitting accuracy (R2 = 0.65, the residual sum of squares (RSS) = 2.65 × 10−4), the nugget (C0) was 0.21, and the spatial structure ratio was 94.0%. It showed that the AGB of footprints had strong spatial correlation and could be interpolated by kriging. Finally, the slope in the topographic variables was selected as the co-interpolation variable, and cokriging spatial interpolation was performed. Furthermore, a continuous map of AGB spatial distribution was obtained, and the total AGB was 6.07 × 107 t. The spatial distribution of AGB showed the same trend as the distribution of forest stock. The absolute accuracy of the estimation was 82.6%, using the statistical value of the forest resource planning and design survey as a reference. The ATLAS data can improve the accuracy of AGB estimation in mountain forests.

1427. Correlation of Dermoscopic and Histopathologic Patterns in Leprosy-a Pilot Study

Abstract Background Leprosy is a chronic granulomatous disease caused by Mycobacterium leprae. It is diagnosed based on clinical features and confirmed on the histological findings and peripheral slit skin smear staining. Dermoscopy is a handy easily accessible tool to diagnose this granulomatous disease and classify patients based on the immunological and clinical response. Methods A total of 50 patients in different poles of leprosy were evaluated as a single spot observational analysis. The clinical and histological findings were correlated with the characteristic dermoscopy findings. A Lepromatous leprosy showing xerosis and scaling along leg as part of glove and stocking distribution of lesions Dermoscopic pattern in lepromatous leprosy showing partial loss of hair follicles, dry xerotic skin, and white characteristic scaling (Heine Delta® 20 T dermatoscope; 16×; polarizing) Results The dermoscopy findings correlated with the clinical and histological findings. Tuberculoid poles of leprosy classically showed loss of hair and skin pigment along with absence of white dots as sweat glands in dermoscopy. Lack of blood vessel changes ruled out any lepra reaction. Lepromatous pole of leprosy on the other hand showed characteristic xerosis and white scaling on dermoscopy in the background of hypotrichosis and hypopigmentation. leprosy reactions were characterized by blood vessel changes and arborizing blood vessels were characteristic in erythema nodosum leprosum and a diffuse erythema was a clue towards diagnosing type I lepra reaction. Interestingly clofazimine induced pigmentation was picked up characteristically on dermoscopy as a ‘honey comb pattern’. Borderline tuberculoid leprosy with a hypoaesthetic patch on the left side of face with a thickened greater auricular nerve Dermoscopic pattern in borderline tuberculoid leprosy showing white areas with loss of hair follicles. In between yellow globules can be seen which was the hallmark apart from white areas demonstrating hypopigmentation. Absence of blood vessels rules out lepra reaction (Heine Delta® 20 T dermatoscope; 16×; polarizing) Conclusion Dermoscopy is certainly a handy tool in aiding the diagnosis of leprosy, lepra reactions and course of therapy. Characteristic patterns during the course of leprosy would certainly facilitate a quick and definitive diagnosis of patients suffering from leprosy. Also patient drug compliance particularly to Clofazimine can also be picked up objectively on Clofazimine. Multiple erythematous plaques on the back depicting type 1 lepra reaction Dermoscopic features of type I lepra reaction showing characteristic diffuse erythematous background and branching telangiectatic vessels along with sparse hair follicles and scaling (Heine Delta®20 T dermatoscope; 16×; polarizing) Disclosures All Authors: No reported disclosures.

Enhancing cooperative responses by regional fisheries management organisations to climate-driven redistribution of tropical Pacific tuna stocks

Climate change is predicted to alter the distributions of tropical tuna stocks in the Pacific Ocean. Recent modelling projects significant future shifts in tuna biomass from west to east, and from national jurisdictions to high seas areas. As the distributions of these stocks change, the relevant regional fisheries management organisations (RFMOs)—the Western and Central Pacific Fisheries Commission (WCPFC) and the Inter-American Tropical Tuna Commission (IATTC)—will need to develop an expanded framework for cooperation and collaboration to fulfil their conservation and management responsibilities under international law. The key elements of a possible expanded framework for cooperation can be developed, and fundamental areas for collaboration identified, by applying and adapting principles established in the United Nations Convention on the Law of the Sea, the United Nations Fish Stocks Agreement, and the constituent instruments of the RFMOs themselves. Our analysis reveals a wide range of important issues requiring cooperation, and three clear priorities. First, a formal mechanism for cooperation is needed to enable effective and efficient decision-making and action by the two RFMOs on key issues. Second, further cooperation is required in scientific research and modelling to better understand the biology and distributions of Pacific tuna stocks and how they will respond to climate change, and to inform stock assessments and harvest strategies. Third, the RFMOs must cooperate to define appropriate limits on fishing for each stock in a way that ensures they are compatible across the two organisations, taking into account their different members and management regimes.

Mapping the social stock and spatiotemporal distribution of high-tech minerals from wasted mobile phones in China: 2001-2019.

In the twenty-first century, mobile phones have become one of the most indispensable electronic products in the international community. The pollution of wasted mobile phones has become an urgent problem worldwide and needs special attention. In this paper, we applied the consumption and usage method to calculate the high-tech mineral elements in China from 2001 to 2019. To analyze the spatial distribution of per capita high-tech minerals in China, we proposed a model (3D GHM) through which a 3D grid of high-tech minerals in wasted mobile phones can be obtained in 1km resolution. The results showed that the total amount of wasted mobile phones in China from 2001 to 2019 was 8.6 billion, with a growth rate of 1026.7% in 2019 compared with 2001. Moreover, the spatiotemporal distribution of wasted mobile phones is characterized by more in the east and less in the west. The total amount of cobalt, palladium, antimony, beryllium, neodymium, praseodymium, and platinum in wasted mobile phones from 2001 to 2019 reached 42,422.4 tons. Based on our results, we proposed a system for efficient collecting and recycling of wasted mobile phones in China.

Lifebuoy Soap Stock Decision Making System Of Neighbourhood 5 And 6 Pagar Dewa Urban Village Bengkulu

A product provider must make the right decisions in predicting the amount of new stock that will be distributed to stalls. Sales of lifebuoy soap in Neighbourhood OF 5 and 6 experienced a difference in the number of sales each month. This of course will make it difficult for the supplier of goods to know the exact number of products that must be stocked. To be able to overcome this and increase the realization of sales from each stall, it is necessary to have a fast and appropriate prediction process that can overcome problems in determining the amount of distribution of new stock. The method used is the Fuzzy Tsukamoto method and is written in the PHP programming language. Where this method is chosen because it is a method of counting with variable words, instead of counting with numbers, human expert systems can be implemented into machine language easily and efficiently. Identification of user needs is needed in the design to determine what features can be used in the system and use story boards to get an overview of the system. System testing using black box by testing all buttons on the application. Based on the results of the study, it can be concluded that this system helps simplify and shorten the time in determining the amount of fulfillment of new stock requests

Temporal and spatial changes in soil organic carbon and soil inorganic carbon stocks in the semi-arid area of northeast China

Soil organic carbon (SOC) and soil inorganic carbon (SIC) has important effects on soil physical, chemical and biological properties. They play an important role in coordinating the relationship between soil water and air, increasing soil water holding capacity and improving plant productivity. In this study, a boosted regression trees (BRT) model was developed to map the spatial distribution carbon stocks in the semi-arid region of Northeast China in 1990 and 2015. During the two periods, 10-fold cross-validation technology was used to test the performance and uncertainty of BRT model. In order to construct the model, 9 environmental variables (derived from climate, topography and biology) and 173 (1990) and 223 (2015) topsoil (0–30 cm) samples were used. The comparison between estimated and observed data shows that the RMSE of SOC and SIC stocks were 0.53 kgm−2 and 0.19 kgm−2 in 1990, and 0.65 kgm−2 and 0.20 kgm−2 in 2015, respectively. Elevation, normalized difference vegetation index, mean annual precipitation and Landsat band 3 were identifies as critical environmental factors for simulating the spatial distribution of SOC, accounting for 76.6 % and 70.3 % of the total relative importance in 1990 and 2015, respectively. Mean annual precipitation, mean annual temperature and topographic wetness index were the critical environmental factors for simulating the spatial variation of SIC during the two periods. Land use change also played an important role in the spatial variability of SOC and SIC stocks. In the past 25 years, soil carbon stocks decreased from 6.2 kg m−2 in 1990 to 5.9 kg m−2 in 2015. The spatial distribution pattern of SOC was high in northeastern area and low in southwestern area during the two periods, while the spatial distribution pattern of SIC was opposite to that of SOC stocks. The mapped soil carbon stock distribution is fundamental to future study of soil carbon cycle and regional carbon balance in semi-arid regions.

Comparison of Random Forest and Kriging Models for Soil Organic Carbon Mapping in the Himalayan Region of Kashmir

The knowledge about the spatial distribution of soil organic carbon stock (SOCS) helps in sustainable land-use management and ecosystem functioning. No such study has been attempted in the complex topography and land use of Himalayas, which is associated with great spatial heterogeneity and uncertainties. Therefore, in this study digital soil mapping (DSM) was used to predict and evaluate the spatial distribution of SOCS using advanced geostatistical methods and a machine learning algorithm in the Himalayan region of Jammu and Kashmir, India. Eighty-three soil samples were collected across different land uses. Auxiliary variables (spectral indices and topographic parameters) derived from satellite data were used as predictors. Geostatistical methods—ordinary kriging (OK) and regression kriging (RK)—and a machine learning method—random forest (RF)—were used for assessing the spatial distribution and variability of SOCS with inter-comparison of models for their prediction performance. The best fit model validation criteria used were coefficient of determination (R2) and root mean square error (RMSE) with resulting maps validated by cross-validation. The SOCS concentration varied from 1.12 Mg/ha to 70.60 Mg/ha. The semivariogram analysis of OK and RK indicated moderate spatial dependence. RF (RMSE = 8.21) performed better than OK (RMSE = 15.60) and RK (RMSE = 17.73) while OK performed better than RK. Therefore, it may be concluded that RF provides better estimation and spatial variability of SOCS; however, further selection and choice of auxiliary variables and higher soil sampling density could improve the accuracy of RK prediction.

Chatter-free milling strategy of a slender Blisk blade via stock distribution optimization and continuous spindle speed change

The machining process of Blisk blades poses multiple challenges due to high requirements on surface quality and precision combined with high dynamic compliance of the thin-walled blades. Avoidance of chatter is thus of high priority in Blisk blade machining. However, the geometry of the Blisk blade array where the tool must fit between individual blades significantly limits the possibilities of controlling stability through the relative orientation of the tool and workpiece. Thus, the main parameters that can be used to control the stability of the process are the distribution of stock allowance and the spindle speed. Due to the effect of material removal on the blade’s dynamic properties, spindle speed needs to be adjusted throughout the machining process to keep it within the continuously changing stability gaps. This paper describes in detail an optimization procedure for the design of stock allowance distribution in such a way that a continuous spindle speed modulation is possible that avoids chatter throughout the machining process by maintaining spindle speeds within stability gaps. The presented algorithm uses finite element analysis software to simulate the effects of stock allowance distribution and material removal on workpiece dynamical properties. This information is then coupled with a stability model based on the Jacobian of the cutting force with respect to the regenerative deflection to identify the varying stability gaps throughout the machining process. The proposed method was experimentally verified.

Effect of planting density on root biomass and distribution, and soil organic carbon stock of Acacia decurrens stands in Northwestern Ethiopia

Background:The expandingAcacia decurrenswoodlots in Northwestern Ethiopia is recognized for carbon storageviaroot biomass and soil organic carbon (SOC) enhancement but its planting densities have varied considerably. This study evaluated the effect of planting density on the root biomass, SOC stock, and vertical distributions in the stands.Methods:Five planting densities (0.5 m x 0.5 m, 0.75 m x 0.75 m, 1 m x 1 m, 1.25 m x 1.25 m, and 1.5 m x 1.5 m) were replicated four times with randomized complete block design. Soil core (6.67 cm diameter) and pit (900 cm2area) methods were used to collect fine and coarse root samples within 0–50 cm soil depth (having five soil layers in 10 cm intervals), respectively. Fine root biomass samples were classified as live and dead (necromass) and further as tree and herbaceous root. All root biomass samples were washed, oven-dried, weighed, and standardized into gram per meter square (g m-2) for root biomass comparisons for each planting density and soil depth, then summed up for 0–50 cm depth as a total root biomass. The vertical distributions of fine and coarse root biomass at each depth were expressed as a percentage (in decimal) of the total root biomass (0–50 cm).Conclusions:Planting density had significant effects on root biomass, SOC stock, and root distributions (P < 0.05) but inconsistent for the percentage of SOC stock at all soil layers except at 40-50 cm. PlantingA. decurrenswith high density is recommended to increase root biomass, SOC, and percentage of roots in deep soil layers. Further study is suggested for the effects of stand age on root biomass dynamics and SOC stock with large scale.

Spatial and in-product density characterization of in-use copper stocks in Japan for stock recyclability assessment

In-use metal stocks comprise various products, and their recyclability is determined by several factors. Hence, a comprehensive characterization of in-use stocks is required for stock recyclability assessment. We characterized in-use copper stocks in Japan by introducing two indicators to represent stock attributes relevant to recyclability: spatial density (SD) and in-product density (PD). SD is based on the spatial distribution of in-use stock, which is estimated by material flow analysis. PD is quantified based on the disassembly tree and level concepts and input-output analysis framework. Infrastructure-related products exhibited a relatively weak correlation with population and low SD, suggesting relatively large efforts required for collection. In contrast, information and communication electronics exhibited higher SD but lower PD, suggesting relatively large efforts required for preprocessing and recovery stages. Furthermore, integrated density characterization demonstrated a trade-off between three aspects related to recyclability: the amount of in-use copper stock, SD, and PD.

Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data

We investigate whether oil-price uncertainty helps forecast the international stock returns of ten advanced and emerging countries. We consider an out-of-sample period of August 1925 to September 2021, with an in-sample period between August 1920 and July 1925, and employ a quantile-predictive-regression approach, which is more informative relative to a linear model, as it investigates the ability of oil-price uncertainty to forecast the entire conditional distribution of stock returns Based on a recursive estimation scheme, we draw the following main conclusions: the quantile-predictive-regression approach using oil-price uncertainty as a predictor statistically outperforms the corresponding quantile-based constant-mean model for all ten countries at certain quantiles (capturing normal, bear, and bull markets), and over specific forecast horizons, compared to forecastability being detected for eight countries under the linear predictive model. Importantly, we detect forecasting gains in many more horizons (at particular quantiles) compared to the linear case. In addition, an oil-price uncertainty-based state-contingent spillover analysis reveals that the ten equity markets are connected more tightly at the upper regime, suggesting that heightened oil-market volatility erodes the benefits from diversification across equity markets.

Estimation and application of spatial distribution of carbon storage in Wushe reservoir watershed based on environmental indicators in Taiwan

The forest land carbon storage assessment model proposed in this study belongs to the IPPC Tier-3 method. The model operates through a conceptual model that includes environmental parameters such as Photosynthesis Index (NDVI), Soil Depth Index (TWI) and Canopy Height Model (CHM). The model is verified by the IPPC Tier-2 method, which can effectively construct the distribution of watershed-scale forest carbon stock. The spatial distribution of carbon fluxes can be obtained from the carbon stock information of the two periods. The carbon flux index can be used to describe the distribution of carbon stocks and carbon emissions in the watershed, and then the location of negative carbon flux (vegetation degradation) can be extracted as a value-added application of vegetation restoration hotspots. The accuracy of the model estimation in forest land verification is high, reaching a significant level of 0.1%, which can faithfully reflect the carbon stock of forest land. However, in non-forest lands, carbon stock estimates tend to exhibit carbon storage potential due to land-use disturbances. A combination of conceptual models and environmental indicators is of great help in assessing watershed carbon stocks and fluxes.