Land Types Research Articles

PEMETAAN JASA EKOSISTEM PENYEDIA PANGAN DI PROVINSI BALI

Ecosystem services are the benefits that humans obtain from ecosystems. With the growing demand to implement sustainable development, the need for information on ecosystem services is increasing as a consideration in various policies and development planning. In response to this need, the method that is often used is the preparation of ecosystem services maps using an approach obtained from land cover data. Many people think this method works well and saves a lot of time and money, especially for studying places on a global, regional, or national level, where it's easy to get data on land cover. The point of this study is to look at how the results of the 2018 and 2022 food supply ecosystem services maps compare. These maps were made by experts who thought about how ecosystem services could be used in different types of land and ecoregions. The Analytical Hierarchy Process (AHP) with the pairwise comparison method is used to figure out how much ecosystem services are worth in relation to land cover and ecoregions. The island of Bali was used as a study area, and food supply was the type of ecosystem service that was looked at. Ecoregion data results for 2022 with the high class being more dominant and having an area of 385,339.19 ha or the equivalent of 66.67%. Land cover in 2018 produced a dominant high class with an area of 288,931.82 ha or the equivalent of 48.74%. The land cover results in 2022 are predominantly high class with an area of 289,039.25 ha or the equivalent of 50.01% of the total area of the island of Bali. The analysis results from the combination of ecoregion and land cover in 2022 are predominantly high class with an area of 182,039.65 ha or the equivalent of 31.49%. Several factors can explain the connection between ecosystem processes and the benefits they provide, which can get around or lessen the problems with using land cover data. Keywords: Ecosystem Services; Expert Judgement; Ecoregion; Land Use Based Proxy

Livelihood Diversity of Rural Communities Without Legal Access to Forest Resources: The Case of Kerinci Seblat National Park in Bengkulu Province

Kerinci Seblat National Park in Bengkulu, Indonesia, was gazetted by the Indonesian government, and its overlaps with forests occupied by most indigenous communities made their farming activities in the area illegal. People were prohibited from accessing and expanding their farming areas in the national park, threatening their livelihoods. The livelihood diversity index (LDI) and livelihood asset index (LAI) were used to explore the livelihood systems of these communities. This study also examines the effect of livelihood assets on livelihood diversity and analyzes livelihood strategy choices using Giddens’ structuration theory. A quantitative survey combined with in-depth interviews was conducted in two villages with different land types: wetlands (rice fields) and drylands (farmlands). This study found that the communities diversified their livelihoods into eight types of livelihood strategies. Almost all livelihood indicators were different, and the differences in livelihood asset indicators affected the LDI. As a process of structuration, communities have diversified their livelihoods into farm (e.g., annual and perennial crops), off-farm (e.g., farm wages), and non-farm (e.g., services and government transfer) activities. Rural households have modified their social and physical structures to secure their livelihoods by optimizing agricultural intensification technologies or by seeking non-agricultural income. Households decide whether to specialize or diversify their livelihoods based on factors such as the area of cultivated land, number of crops cultivated, distance of the farming location from the house, total household income, non-farm income, and reciprocal relationships.

Shea tree (Vitellaria paradoxa C.F. Gaertn.) agroforestry systems in Northern Ghana: population structure, management of trees and impact of below canopy microclimate

The shea tree (Vitellaria paradoxa C.F. Gaertn.) is an important tree species in agroforestry systems in West Africa and shea nuts constitute a fundamental resource for rural livelihoods in this area. This study investigated the sustainability and interactions in agroforestry systems of shea trees around the village Nakpalli in Northern Ghana. The focus of the study was the population structures and densities of shea trees on different land types, below-canopy microclimate and co-cultivation of yams (Dioscorea rotundata (Poir.) J. Miége) under shea tree canopies, and water stress of the trees in the driest season. Shea tree populations are overall well-conserved in this area, but Weibull-distributions of the tree populations and quantification of seedlings showed a lower tree density in both cultivated and fallowed lands, as compared to undisturbed bushlands. Although farmers may deliberately manage the density of larger trees, the low densities of seedlings and saplings indicate that intensified management practices, including shortened fallow periods and intentional clearing of land by fire before sowing, might negatively affect the long-term regeneration of the shea trees. Co-cultivation of yams below shea tree canopies allowed production of 11.5 t/ha as compared to 20.8 t/ha at open field conditions. The lower yields may have been caused by an almost 74% reduction of photosynthetically active radiation below canopies, relative to outside the canopies. Shea trees in the fields, fallows and bushlands had close-to-zero predawn leaf water potentials, indicating low water stress, even in the middle of the dry season. Thus, shea trees are both well-adapted and highly valued in this area, which underlines the importance of conserving this indigenous tree species in the agroforestry systems of northern Ghana.

Spatio-temporal variations and influencing factors analysis of coastal wetlands in Tianjin, China

Coastal wetlands are one of the world’s most threatened ecosystems and the influences of climate change and anthropogenic factors on changes in coastal wetland distribution have been the subject of active research in recent years. However, the multi-year intergenerational trends in coastal wetland areas, and the factors influencing them in China have not been fully studied using geographic spatial data during the past 30 years. The relative contributions of climate change and anthropogenic factors to spatio-temporal variations in coastal wetland area also remain to be described. In this study, we discuss changes in the coastal wetland areas and the reasons behind them in Tianjin, which is one of China’s fastest developing regions, using remote sensing and geographic information system technology, Pearson correlation analysis, the relative weight method and the land expansion extraction module, the land expansion analysis strategy (LEAS) model of the Patch-generated Land Use Simulation (PLUS) model. The results showed that the total wetland area declined from 2233.59 km2 in 1984 to 1742.73 km2 in 2020. We conclude that the expansion of non-wetland land types is the main driver of natural wetland area decrease, with 830.86 km2 of natural wetlands having been converted to non-wetlands during this period. The large areas of shallow water and tidal marsh that have been converted to construction and bare land particularly emphasize the primary importance of urbanization and coastal reclamation in driving wetland reduction. The results showed that the temporal variation of natural wetlands area was correlated with population density (PD), total gross domestic product (GDP), annual mean temperature (AMT), average relative humidity (ARH), and primary (PI), secondary (SI), and tertiary industrial development (TI). PD, PI, TI, GDP, SI, AMT, and ARH contributed to 24.47 %, 18.21 %, 15.74 %, 14.16 %, 12.77 %, 7.09 %, and 4.86 % of the wetland area decrease, respectively. PD, distance to settlements (DS), distance to railways (DRW), AMT, distance to rivers (DR), and GDP contributed 17.61 %, 14.27 %, 13.83 %, 13.62 %, 12.07 %, and 10.92 % of the spatial variations of natural wetland area, respectively, which showing the predominant effects of anthropogenic variables on the spatio-temporal natural wetland areas. Our results are valuable in identifying the dynamic spatio-temporal variations in coastal wetlands to improve our understanding of the impacts of climate change and human activities on coastal wetlands to help in the future protection and restoration of wetlands.

Tanggap Morfofisioligi Beberapa Varietas Kedelai di Lahan Pasang Surut Tipe C

This research aims to look for the best morphophysiology response of soybean varieties in the tidal land type C. Research activities conducted in Kalimas Village Subdistrict Sungai Kakap, Kuburaya District from November 12th 2017 to February 10th 2018. Methode used is Randomized Block Design (RBD) with 6 factors, there were A: Burangrang varieties, B: Anjasmoro varieties, C: Argomulyo varieties, D: Dena 1 varieties, E: Gema varieties and F: Dering 1 varieties. Each factor replicated four times, so there were 24 experimental units. Variables measured were plant height, root volume, number of effective root nodules, dry weight of plants, number of chlorophyll, flowering age, harvest age, number of productive branches, number of pods per plant, number of seeds per pod, dry weight of 100 seed, dry weight of seed per plot. The result showed that morphophysiology response of some soybean varieties in the tidal land type C indicates a difference on number of effective root nodules, number of chlorophyll, flowering age , harvest age, number of pods per plant, number of seeds per pod, dry weight of 100 seed and dry weight of seed per plot.

From meteorological to agricultural drought: Propagation time and influencing factors over diverse underlying surfaces based on CNN-LSTM model

As global warming intensifies and extreme weather events become more frequent, the severity of drought conditions in China's Xinjiang region has escalated. This exacerbates socio-economic pressures in the area and presents increasingly formidable challenges for the future. In response to these challenges, researching drought phenomena in Xinjiang is imperative. This study employs Bayesian methods and copula functions to estimate drought propagation time. It utilizes a hybrid deep learning model (CNN-LSTM) to analyze the process of drought propagation and its influencing factors across four land cover types: crops, forest land, grassland, and unused land. The findings indicate that Cropland experiences the longest average time of drought propagation (5.27 months), while forests have the shortest duration (4.2 months). Unused land and grassland exhibit similar average durations of propagation (4.8 months). On an annual scale, drought propagation time for each land type manifests in two phases: from January to May and from June to December. The former phase shows propagation time ranging from 6 to 9 months, while the latter ranges from 1 to 5 months; both demonstrate an increasing trend over time. Seasonally, all Land Cover Types exhibit a pattern of shorter propagation times in summer and autumn compared with winter and spring. Moreover, a longer time of drought propagation correlates with a greater disparity between meteorological and resultant agricultural drought severity. In analyzing the influence of factors on drought propagation, soil moisture content and El Niño-Southern Oscillation(ENSO) were found to significantly impact all Land Cover Types, progressively strengthening their influence over the years.

Impact of land-use change on ecological vulnerability in the Yellow River Basin based on a complex network model

The Yellow River Basin in China, which is characterized by significant soil erosion and arid to semi-arid conditions, has experienced severe ecological issues due to prolonged excessive development and land-use changes. Studies on ecosystem vulnerability have become a major basis for supporting the sustainable and healthy development of watershed ecosystems. Based on the land-use data of 2000, 2005, 2010, 2015, and 2020, this study used a complex network model to identify the key types of land-use transformation in the Yellow River Basin. The cascade failure model was used to evaluate the impact of land-use transformation on ecological vulnerability in the Yellow River Basin of China. The land-use changes in the Yellow River Basin from 2000 to 2020 exhibit significant heterogeneity in both quantity and direction. Among them, the total area of agricultural land showed a downward trend as a whole, and the area rebounded slightly from 2000 to 2015. The growth trend of construction land area is obvious, with a year-on-year increase of 46.81 % in 20 years. Through network identification, we found that ecological land types such as forest, grassland, and dryland are the primary factors contributing to land area outflow. Conversely, artificial land types including urban land, rural residential land, and other built-up land predominantly serve as factors for land area inflow. The Yellow River Basin experiences frequent land-use transitions, resulting in the poor stability of the land transfer network. However, the study reveals that the ecosystem service value increases as the areas of paddy fields, dryland, urban land, rural residential land, and bare land decrease; this trend contributes to mitigating ecological vulnerability. To ensure the overall stability of the ecosystem and implement healthy and sustainable development, the maximum reduction in the areas of dryland, forest, paddy, and grass should be limited to 40 %, 30 %, 50 %, and 50 %, respectively, in future planning and design processes. In conclusion, the land-use transformation in the Yellow River Basin of China has profound implications for ecological vulnerability. The research findings can provide valuable references for future ecological research on areas facing similar challenges in protecting ecological fragility.

Association Analysis of the Spatial and Temporal Changes in Vegetation Photosynthesis Levels with Land Cover Changes in China Based on Solar-Induced Fluorescence

Understanding the relationship between vegetation photosynthesis levels and land use changes is crucial for assessing ecosystem health and plant growth status. Existing studies have not fully considered temporal and spatial dimensions, resulting in an incomplete understanding of the relationship between vegetation photosynthesis levels and land use. Based on solar-induced fluorescence (SIF) data from 2001 to 2022, this study used the Mann-Kendall (MK) test and spatial association analysis to explore the associations between temporal and spatial changes in vegetation photosynthesis levels and land cover change (LCC) in China. The contributions and findings are as follows: (1) A computational framework was utilized to comprehensively measure the spatial correlation between LCCs and chlorophyll levels based on their spatial co-occurrence. (2) The MK test results of the annual and monthly average vegetation photosynthesis levels revealed that most regions in China exhibited increasing trends, accounting for 90.01% and 91.78%, respectively. Moreover, the vegetation photosynthesis levels in western China had a downward trend, indicating that the vegetation ecosystem in this region may be under a certain degree of pressure or may face the risk of degradation. (3) Some economically developed provinces are facing ecological pressures caused by urbanization and industrialization, which have led to the degradation of vegetation ecosystems and a decrease in vegetation photosynthesis levels. (4) Highly supportive areas of the land use–vegetation photosynthesis level association analysis were mainly distributed in grassland and forest areas, indicating the effectiveness of forest protection and grassland management policies. Moreover, the decrease in vegetation photosynthesis mainly occurred in barren areas, illustrating that the management and protection of this type of land still need to be strengthened. These findings underscore the complex interplay between land use and vegetation health, providing insights for sustainable land management policies.

The historical ecological background of West Nile virus in Portugal indicates One Health opportunities

West Nile (WNV) is a zoonotic arbovirus with an expanding geographical range and epidemic activity in Europe. Not having yet experienced a human-associated epidemic, Portugal remains an outlier in the Mediterranean basin. In this study, we apply ecological niche modelling informed by WNV historical evidence and a multitude of environmental variables from across Portugal. We identify that ecological backgrounds compatible with WNV historical circulation are mostly restricted to the south, characterized by a warmer and drier climate, high avian diversity, specific avian species and land types. We estimate WNV ecological suitability across the country, identifying overlaps with the distributions of the three relevant hosts (humans, birds, equines) for public and animal health. From this, we propose a category-based spatial framework providing first of a kind valuable insights for WNV surveillance in Portugal under the One Health nexus. We forecast that near future climate trends alone will contribute to pushing adequate WNV ecological suitability northwards, towards regions with higher human density. This unique perspective on the past, present and future ecology of WNV addresses existing national knowledge gaps, enhances our understanding of the evolving emergence of WNV, and offers opportunities to prepare and respond to the first human-associated epidemic in Portugal.

Changing urban land types and its locational impact on groundwater resources: a case study on Megacity Kolkata

Changing urban land types and its locational impact on groundwater resources: a case study on Megacity Kolkata

Tracking dynamics characteristics of tidal flats using landsat time series and Google Earth Engine cloud platform

Tidal flats serve as vital spatial resources within coastal wetlands and play crucial roles in biological habitat preservation, environmental conservation, and human development. However, accurately delineating their extent from instantaneous remote sensing images poses challenges, owing to the dynamic interplay between seawater and land. Therefore, this study utilized the consistency of remote sensing satellites and developed a multi-feature decision approach based on the long-term remote sensing datasets and the Google Earth Engine (GEE) cloud platform for determining the spatial extent, classifying types, and mapping the spatial-temporal distribution of the tidal flats. Initially, a multi-temporal image stack was compiled from the filtered remote sensing images. Subsequently, the modified normalized difference water index (MNDWI) and automated water extraction index (AWEI) were calculated to establish the maximum and minimum water surfaces using the extreme value composite algorithm (EVCA). The Otsu algorithm and spatial overlay analysis method were then utilized to accurately delineate the spatial extent of the tidal flats. Additionally, the Normalized Difference Vegetation Index (NDVI) was utilized to accurately identify tidal flat types. Post-processing involves elevation data and mathematical morphological methods to mitigate the impact of permanent water bodies. Finally, the accuracy of the extracted spatial extent and types of tidal flats was evaluated. The efficacy and practicality of the proposed method were validated using the Zhoushan Archipelago and Landsat time series in China. The results revealed the following: (1) the acquired tidal flat information exhibited evident boundaries and accurate types, achieving an overall accuracy (OA) of 94.80 % and a Kappa coefficient of 0.89; (2) the area of tidal flats in the Zhoushan Archipelago increased from 2,182.19 ha in 1985 to 3,761.21 ha in 2020, with an average annual increase of 45.12 ha and an average annual increase rate of 1.57 %; and (3) over 35 periods, the area transformed from other land types to tidal flats amounted to 2,895.74 ha, while the area converted from tidal flats to other land types totaled 1,651.90 ha. The three islands with the most rapid growth in tidal flat area were Liuheng Island, Dachangtu Island, and Daishan Island, with changes of 675.68 ha, 380.47 ha, and 362.63 ha, respectively. This method can offer an automated, swift, and accurate approach for tidal flat extraction, demonstrating high precision and practical effectiveness, thereby providing robust technical support for coastal resource surveys.

The barrier risk to the ecological connectivity of plant diversity in karst landscapes in Guizhou Province, China

Ecological connectivity in landscapes is crucial for plant diversity conservation. The barrier risk to ecological connectivity represents the risk to ecological connectivity loss or weakening, resulting from the barrier to biological information exchange among habitats. Therefore, clarifying the barrier risk to the ecological connectivity of plant diversity in space can reveal the spatial impacts of reduced ecological connectivity on plant diversity. This study analyzed effects of karst peak, river network, arable land, and impervious surface on plant diversity in karst natural, countryside, urban, and island landscapes in Guizhou Province with fragile environment. Then, we calculated the barrier distance of ecological connectivity to reveal the barrier risk to the ecological connectivity of plant diversity in space. The results showed that karst peak was the source of high plant diversity, and plant diversity could diffuse about 400 m around karst peaks. River network and arable land enhanced the connectivity among karst peaks to maintain plant diversity, and the effect on enhancing the connectivity was about 300 m and 450 m, respectively, while the weakening effect of impervious surface on connectivity was about 350 m. Based on the distance for plant diversity diffusing around karst peaks, the barrier distance of ecological connectivity was determined by the combination type of river network, arable land and impervious surface in landscapes. From low to high, the barrier risk to the ecological connectivity of plant diversity was about 1,110 m in the combination of river network and arable land, about 790 m in the combination of river network, arable land and impervious surface, about 520 min the combination of arable land and impervious surface, about 400 m in the combination of river network and impervious surface. Our findings clarify the barrier risk to the ecological connectivity of plant diversity in space, and provide a scientific basis for plant diversity conservation from the perspective of ecological connectivity.

The Impact of Marketing in Increasing the Level of Competitiveness for Agro-Food Products in Albania

The climate that prevails in Albania and the type of agricultural land are favorable for new cultures and agricultural products that have higher benefits than other products that have been cultivated so far. Developing and increasing the capacities of existing products is one of the main components in a small or medium-sized company. A progressive company should preemptively address the planning and expansion of its product range and diversity of culture where it operates in order to remain competitive in the market. To achieve this, companies nowadays need to implement the most effective marketing strategies. Marketing is increasingly emerging as the most significant aspect for companies in the agro-food sector, serving as the primary means of customer orientation, with arguments as to why they should choose a company's products or services over other competitors. With the advancement of technology, the utilization of marketing and its elements is increasing more and more, as the best way to achieve the desired profit, target performance and competitiveness in the market. The purpose of this paper is the analysis of the existing situation in the development of the competitiveness of agro-food products as a result of the application of marketing, through which the market will be studied and make the agricultural producer aware of the increase of their performance in the market, through the production of quality and cost-effective products. The results reveal that agro-food production companies and farms have started to apply marketing in various forms, both in social and traditional media, creating better competitive positions in the market and increased production capacities allowing for the substitution of imported products with local products. Consequently, it has influenced the increase in consumer confidence in Albanian products and brands.

Identification of Leaf Diseases of Different Crops using modified ResNet50

Every country’s income depends heavily on the agriculture sector. Agriculture output is influenced by a wide range of factors, including crop health, weather, water availability, and type of land. Low output is primarily caused by crop disease. The Identification and treatment of diseases early on are very crucial. Traditional approaches don't offer a reliable evaluation. The spread of the disease must be determined using automated techniques. One of the cutting-edge technologies that aids in automating disease detection is deep learning. Deep learning has been used in numerous studies to detect crop diseases. The goal of this research is to effectively diagnose leaf diseases in all major crops using a novel deep learning model using a modified ResNet50. The research employed different deep learning models like VGG16, Inception V3 and modified ResNet50 on publicly available dataset of plant village. A novel approach has been proposed by extracting features from different models. The ResNet50 uses the skip connection which is considered to training and test error. The modified ResNet50 model helps add diversity in different crops for providing accuracy across all crops on public dataset of plant village. The dataset was obtained from a publicly available database on Kaggle. The dataset contains 13 different crops and a total of 38 diseases classes. On modified plant villages the proposed model generated a very good accuracy of 99.49% with precision of 0.966 and f score of 0.995. The proposed model is reliable for the classification of various leaf diseases in all the major crops.

Comprehensive analysis of Perilla frutescens (L.) Britt. along the value chain in northeast Inner Mongolia

Abstract Objective To ensure the quality of Perilla frutescens (L.) Britt. and improve the associated benefits for stakeholders, this study analyzed the influences of different circulation channels and stakeholders on the quality, price, and other factors of P. frutescens with consideration to P. frutescens distribution. Method We interviewed the local stakeholders and e-commerce platforms in Oroqen Autonomous Banner and Morin Dawa Daur Autonomous Banner regarding the origin, circulation, distribution, and prices of different medicinal parts of P. frutescens. In addition, the maximum entropy model was used to predict the potential distribution of P. frutescens in the study area. According to the Chinese Pharmacopeia (2020 edition), we measured the content of index components in the collected Perillae Folium, Perillae Caulis, and Perillae Fructus samples and evaluated the quality of the samples by quantitative and cluster analyses. Remote sensing was employed to distinguish and calculate the P. frutescens area in highly suitable regions. The autoregressive integrated moving average model was adopted to analyze the Perillae Fructus price in the study area. Result The results showed 8 value chains for P. frutescens. The cooperation chain between farmers and enterprises in the study area could maximize the benefits for all stakeholders and guarantee the quality of the medicinal materials. The results of the regionalization analysis showed that the most suitable area for planting P. frutescens was the junction between Oroqen Autonomous Banner and Morin Dawa Daur Autonomous Banner. Chemical results showed that Perillae Fructus and Perillae Caulis samples were unqualified and mostly purchased from e-commerce platforms. We identified 5 land types, among which the cultivated land area was 3247.7501 km2. The price of Perillae Fructus in the study area showed a rising trend, although this trend slowed down. Conclusion This study involved various links in the production and circulation of medicinal materials from planting to consumption by consumers, which can help to facilitate the future research on any link. The findings help to guarantee the quality of medicinal materials and benefits of all stakeholders and promote the development of the P. frutescens industry in the study area.

LAND AND PROPERTY RESOURCES OF AGRICULTURAL ENTERPRISES IN THE SYSTEM OF THEIR RESOURCE POTENTIAL

The article is devoted to the justification of the organizational and economic principles of management and rational use of land and property resources and the determination of the principles of their effective combination based on the study of modern determinants of the development of the resource potential of agrarian enterprises. The meaning and role of property resources in the activity of agricultural enterprises are revealed, and their components and importance for ensuring the technical base and efficient production processes are defined. It is substantiated that the modernization of the technical park and the improvement of technological processes help to ensure the competitiveness of agricultural enterprises, reducing costs and increasing the quality of products. Land and property resources are defined as the basis of the resource potential of agrarian enterprises, and their proper management and continuous improvement are critical factors of enterprises' sustainable development in the modern conditions of the market environment. The need for a complex approach to managing land and property resources, which considers the specifics of the industry, regional features, and modern trends, has been proven. A comprehensive approach to effectively managing agricultural enterprises' land and property resources is considered. The importance of developing development strategies, implementing advanced technologies, and improving staff qualifications is substantiated. It is noted that strategies such as crop rotation, agroecological monitoring, energy efficiency, and digitalization can be used to optimize the use of resources. These measures contribute to increasing the efficiency of agricultural enterprises in modern conditions. It is established that the context of the land use management system should pay special attention to the basic principles crucial for its effectiveness. Scientific approach, objectivity, economic justification, availability of feedback, consideration of regional specifics, and differentiated application to different types of land stand out among the main principles.

Analysis of rice paddy farmers' perceptions of subsidized fertilizer policy on tidal and irrigated land

This study aims to analyze farmers' perceptions of subsidized fertilizer policies, on tidal and irrigated land. The research was conducted on 2 types of paddy fields, namely tidal land in Tanjung Lago District, Banyuasin Regency and irrigated land in Buay Madang District, East Ogan Komering Ulu Regency, South Sumatra Province, Indonesia. The sampling technique was Simple Random Sampling, which obtained a sample of 50 respondents in each type of tidal and irrigated land, so that the total sample was 100. Then the respondents were interviewed using a questionnaire. The data were analyzed descriptively quantitatively using 4 indicators of the effectiveness of subsidized fertilizer policies, namely the right price, right place, right amount, and right time. The results showed that the right place and right time indicators were effective in tidal land, but the right price and right amount indicators were not effective. On irrigated land, the right price and right place indicators are effective, but the right amount and right time indicators are not effective.

Interregional Flows of Embodied Carbon Storage Associated with Land-Use Change in China

With the continuous expansion of regional trade, interregional teleconnections have an increasingly pronounced impact on the changes in carbon storage caused by land use in China. Current research in this area remains remarkably limited, however. This study employs land-use data, carbon density data, and a multiregional input–output model to precisely quantify the embodied flow and spatial patterns of land-use carbon storage in China. We found that the carbon storage embodied in interprovincial trade in China accounts for 34.9 percent of total carbon storage, with cropland (44.9 percent) and woodland (43.6 percent) representing the highest proportions within their land-use categories. Inner Mongolia, Heilongjiang, and Tibet were found to be the most externally driven in terms of land-use-related carbon storage, with outflows exceeding 2,000 Tg C. Beijing, Tianjin, and Shanghai, on the other hand, were shown to consume up to 90 percent of land-use-related carbon storage inflows, showcasing the strongest external dependence. Additionally, Hunan (1,300.5 Tg C), Hubei (863.4 Tg C), Henan (1,534.6 Tg C), and Shanxi (2,223.6 Tg C) are the provinces where changes in land-use carbon storage are most significant, exerting the greatest influence on changes in China’s total carbon storage. China’s international export of land-use-related embodied carbon storage decreased by 3,964.7 Tg C during the study period, with woodland (1,516.8 Tg C) and grassland (1,505.7 Tg C) being the primary declining land types. Interestingly, as land utilization efficiency continues to rise, over half of the provinces have seen an increase in export trade value, while their corresponding embodied carbon storage has declined. The findings not only unveil the complex dynamics and spatial distribution at work in China’s embodied land-use-related carbon storage but also provide practical insights and directions for achieving carbon neutrality goals.

Hydrochemical and isotopic characteristics of water sources for biological activity across a massive evaporite basin on the Tibetan Plateau: Implications for aquatic environments on early Mars

Covered by vast eolian landforms, gravel deposits, and playas, the worldwide typical evaporite deposit land, Qaidam Basin, in northwestern China is analogous to early Mars when the aridification process had lasted for millions of years since the end of a wetter climate. This study aims to investigate the chemical and isotopic characteristics of waters in an evaporite-rich environment, as well as the habitable conditions therein, that have undergone a transformation similar to early Mars. In May 2023, a total of 26 water samples were collected across the representative central axis of a longitudinal aridity gradient in the Qaidam Basin, including categories of meteoric water, freshwater, standing water accumulated after precipitation, salty lacustrine water, and hypersaline brines to inspect compounds made up of carbon, nitrogen, phosphorus, sulfur, halogen, and metallic elements. As evaporation intensified, the salt types transformed from HCO3-Ca·Na to Cl·SO4-Na or ClMg. The dominance of carbonate will gradually be replaced by sulfate and chloride, leaving much more dilute and less detectable contents. The presence of trace ClO4−, ClO3−, ClO2−, and BrO3− was confirmed in a few of the sampled Qaidam waters, indicating the preservation of oxyhalides in waters within an arid region and possibly the presence of relevant microbial enzymes. The isotopes of water, carbonaceous, and nitrogenous compounds provide valuable references for either abiogenic or biogenic signatures. With undetectable amount, phosphorus was found to be the limiting nutrient in evaporative aquatic environments but not necessarily antibiosignatures. Overall, these results suggest that the paleo-lacustrine environments on Mars are more likely to preserve biosignatures if they feature the dominance of carbonate minerals, bioavailable nitrate, phosphorus, and organic carbon, the presence of thermodynamically unstable oxyhalides, and isotope ratios that point to the involvement of biological activity.

Effect of Soil Texture on Agricultural Machine Performance in Sylhet, Bangladesh.

Soil texture is one of the primary soil physical properties that largely affects agricultural machine performance. Before implementing an agricultural machine at the farm level, it is important to test the machine to gain an understanding of its technical functionality and economic viability to get the best output from it. The research was carried out to assess how soil texture influences the performance of machinery, aiming to determine the effectiveness of agricultural equipment on a particular type of land. Soil samples were collected from nine different fields, and their textures were determined using hydrometer analysis. To correlate soil textural classes with machine performance, machinery data—effective field capacity, forward speed, and field efficiency—were calculated by operating a combine harvester on the study areas during the harvesting season of Boro rice. Two types of soil were identified: loamy sand and sandy loam. The findings of the study showed that machine efficiency has a positive correlation with sand proportion and a negative correlation with clay and silt fractions. It was observed that soil with loamy sand-type textural classes demonstrated better field efficiency, higher effective field capacity, and higher forward speed compared to sandy loam soil. Small and irregularly shaped fields also caused variation in performance. The study identified significant variation in speed between these two types of soils but no significant effect on effective field capacity or field efficiency at the 5% level of significance. The outcomes of this research will help farmers make informed decisions when selecting appropriate equipment for their agricultural operations.