Field Survey Data Research Articles

Ecosystem Structure and Function in the Sea Area of Zhongjieshan Islands Based on Ecopath Model

Based on the field survey and reference data of the sea area of the Zhongjieshan Islands from 2021 to 2022, the Ecopath model was used to analyze the energy flow structure of the marine ecosystem of the sea area of the Zhongjieshan Islands; the energy structure of the marine ecosystem was divided into 21 functional groups, and its nutrient structure, energy flow, and total system characteristics were analyzed. The results show that the credibility of the model is 0.414, which is at a medium level. The trophic level of each functional group of the ecosystem in the sea area of Zhongjieshan Islands was 1–3.48, the energy flow structure of the system was mainly concentrated in the first five grades, and the trophic level was relatively simple, with the average energy transfer efficiency of the system being 8.11%, the energy flow range being 2.81–13.04%, the energy transfer efficiency of the primary producers of the system being 7.25%, and the energy conversion efficiency of the system debris being 9.12%. The total system throughput was 2125.96 t·km−2; The analysis of the overall characteristics of the ecosystem showed that the system connectance index and the system omnivory index were 0.45 and 0.24, respectively, while the Finn’s cycling index was 8.24, the Finn’s mean path length of the system was 2.72, and the total primary production/total respiration was 1.71. In this study, the marine ecosystem model of the sea area of the Zhongjieshan Islands was studied to understand the trophic structure and ecosystem status of the sea area, which is conducive to the sustainable utilization and scientific management of fishery resources in the sea area.

Optimizing rural waste management: Leveraging high-resolution remote sensing and GIS for efficient collection and routing

Accurate assessment of distribution patterns and dynamic insights into rural populations is pivotal for comprehending domestic waste generation, recycling, and transportation in rural territories. Given that the dispersion of rural inhabitants exhibits minimal variation and maintains stability, this research endeavors to establish a pragmatic model for rural domestic waste collection and routing, leveraging the capabilities of very high-resolution remote sensing combined with geographic information system (GIS) techniques. Specifically, the Dilated LinkNet model was employed to discern features such as buildings, roads, water bodies, farmlands, and forests from the high-resolution remote sensing imagery. A novel multiple K-means clustering approach was devised for building segmentation. Within these clusters, an assortment of spatial regulations and evaluations facilitated the judicious selection of environmentally-conscious waste collection sites (WCSs). The Pointer Network, augmented with reinforcement learning, executed a traveling salesman analysis on these chosen WCSs, yielding the optimal collection trajectory. Validated in Huangtu Town, a quintessential rural region in China, our model manifested superior recognition precision, recording IoU accuracies of 0.902, 0.926, 0.933, 0.891, and 0.849 for buildings, roads, water bodies, farmlands, and forests respectively. Notably, when compared to our field survey data, the optimized daily collection route in a rural context decreased from 256.40 km before optimization to 140.44 km, reflecting a substantial reduction of 45.23% in total distance. This study furnishes an effective model that relies solely on information from remote-sensing images for efficient rural waste collection and extends invaluable insights to planners and administrators in the realm of rural and township waste management.

Farmer’s Perception and Determinant of Horticultural Crops in Nagaland and Manipur States

Background: The present research work was undertaken to known about the farmer perception and determinant as the adoption of the horticultural crops and major production constraints faced by them in Nagaland and Manipur states. Methods: For the present study by selecting 100 respondents each from Nagaland and Manipur states to have 200 respondents in total by using purposive stratified simple random sampling technique with the help of data collected through personnel interview methods during the Agricultural calendar year 2019 to 2022 (contain 3 years survey field data). Result: About the farmer perceptions for the horticultural crops in the study area viz; pineapple and chili both were selected due to the prominent crops; based on benefit-cost ratio pineapple crops of Nagaland was recorded as highest (3.31:1) returns, followed by pineapple crop of Manipur (3.01:1) state; also based on benefit-cost ratio, chili crop of Manipur was recorded highest (2.70:1) returns, followed by chili crop of Nagaland (2.76:1) state, respectively. About the perception level it increase by maximum 17.00 per cent for Dimapur Pineapple, followed by Thoubal Chili was 16 per cent, Kohima Chili was 12.00 per cent and minimum Senapati Pineapple was 10 per cent, respectively. About the major constraints faced by the respondents during the production, the foremost was due to the need for high investment in inputs, followed by the size of the land holding and lack of technical knowledge, respectively.

An improved optical trapezoid model to identify wetlands and irrigation water ponds in the arid irrigation district using Google Earth Engine

ABSTRACT In arid regions, wetlands support ecosystem with high biodiversity and productivity. Meanwhile, irrigation during the fallow period often results in the temporary formation of water ponds in the cropland, which plays a critical role in agricultural productivity. The prompt identification of wetlands and irrigation water ponds in irrigation districts is important for the protection of local wetland ecosystem and the effective management of irrigation water. Utilizing the OPtical TRApezoid Model (OPTRAM) for soil moisture estimation, we have proposed an improved version of OPTRAM aimed to identify wetlands and irrigation water ponds in irrigation district using Sentinel-2 data through Google Earth Engine platform. Different criteria were used for the identification of wetland and irrigation water pond, given the greater diversity associated with wetlands. Parameters for the wet edge determined from OPTRAM were used to identify wetlands, while an additional threshold was added to the model and calibrated in accordance with the irrigated area to identify irrigation water ponds. The improved OPTRAM was applied in Hetao Irrigation District (HID) of Northwest China from 2016 to 2023, where autumn irrigation applied in late autumn after crop harvesting was considered. The identified distributions of wetland and autumn irrigation were validated with observations from field survey and statistical data, and were also compared with other remote sensing products. Results show that the proposed model is effective in identifying both wetlands and irrigation ponds. Considering the wetlands, the distances from identified boundaries to the actual boundaries obtained from field surveys were calculated, revealing the mean absolute error of 6.99 m, alongside a validation accuracy ratio of 0.94 for points located within wetlands. For autumn irrigation extent, the overall accuracy is 0.90 based on the observations from field survey, with mean absolute relative errors for irrigated areas across four sub-irrigation districts recorded as 20.55%, 8.10%, 12.83%, and 11.38%, respectively, when compared with statistical data. The majority of wetlands within HID are small in size and scattered, with different trends observed in the wetland areas of sub-irrigation districts and Wuliangsuhai Lake. Autumn irrigated croplands are mainly concentrated in Jiefangzha sub-irrigation district while being scattered across other sub-irrigation districts, depicting an overall decreasing trend in the autumn irrigated area. In summary, the proposed model performed well in identifying both wetlands and irrigation ponds, and can offer valuable support for the conservation of wetland ecosystem and irrigation management.

Determination of effects of climate change on hydropower generation at Kamburu dam-Kenya.

This study aimed to determine the effects of climate change on hydropower generation at Kamburu Dam, Kenya. Kamburu power plant has been experiencing low volumes of water with the shortage of rainfall from its catchment area. This study primarily utilised rainfall and temperature data, as well as field survey data collected through questionnaires. Primary data was collected using questionnaires, photography, checklists, and observation guides. Secondary data sources included Kengen and the meteorological department's annual reports. The study used simple stratified sampling. The four villages of the Kivaa sub-location were sampled into 20 households, making a total of 80 households; Kengen and meteorological stations sampled every 10 respondents to make a total of 100 respondents. Collected data from the questionnaires were coded and analysed using SPSS 29. The results of this research showed that the area experiences increasing temperatures of 0.044? every year and decreasing rainfall of 0.5897mm every year. The research forecasted a decadal increase in temperature of 0.44? and a decadal decrease in rainfall of 5.897mm. The research also showed a decrease in hydropower of 18,790MWH every year, translating to a decadal decrease of 187,790MWH. The research concluded that climate change has greatly affected hydropower production at the Kamburu Dam power plant. The research recommends afforestation and re-afforestation activities, putting rules and regulations of watershed management, upgrading the Kamburu dam infrastructure to fit climate-resilient, expanding the capacity of the dam, and energy storage, among others.

An improved framework for mapping and assessment of dynamics in cropping pattern and crop calendar from NDVI time series across a heterogeneous agro-climatic region.

The absence of spatial and temporal cropping information in semi-arid regions poses a significant challenge in assessing the dynamics of agricultural systems at river basin scales. Satellite remote sensing provides qualitative and quantitative information to derive vegetation dynamics over extensive areas of inherent complexities due to limitations in the availability of field data and the diverse nature of agricultural cropping practices. Utilizing phenological information derived from MODIS Normalized Difference Vegetation Index (NDVI) time series data from 2003-2004 to 2021-2022, this study derives major crop types, and cropping calendar (sowing, maturity, and harvest dates) for each season and year at 250-m resolution. This study introduces an integrated function-fitting model based on the Fast Fourier Transform (FFT) and a Lagrangian 3-point derivative-based approach to extract phenological events from the NDVI time series automatically. The derived phenological information is used in a hybrid crop classification algorithm that combines a rule-based decision tree approach (using the phenological events/dates) and a random forest classifier (using the phenological metrics) to generate the classified crop map at a river basin scale for multiple seasons and years. The implemented approach successfully captured sowing and harvesting dates for every crop growing season over 19years, with an RMSE of 9days, as observed with the available field survey data from 2015 to 2021. The classification results from this hybrid approach demonstrate an overall 82% accuracy. The proposed method shows a substantial improvement in cropping area estimation with a 60% reduction in MAE and RMSE compared to the existing algorithm. From the long time series of derived seasonal crop data (19-year analysis period), the influence of monsoonal activities and shifts on the spatial and temporal dynamics of sowing time and cropping patterns are assessed for a large river basin, demonstrating the utility of this continuous crop calendar. Further, an extensive analysis of results highlights farmers' adaptive strategies in response to dry and wet years, providing foundational insights for future studies on assessing the impacts of climate change. Hence, the hybrid framework adopted in this study for deriving a continuous crop calendar holds immense relevance for parameterizing and utilizing such information for developing river basin scale hydrologic and crop growth models for water resources planning and assessment.

Research on the gravity sedimentation law of watery crude oil in large oil tanks

ABSTRACT Based on field survey data, a numerical simulation method that combines an indoor settling experiment with the Mixture multiphase flow model and the Population Balance Model (PBM) was adopted in this article to study and analyze the sedimentation law of water-containing crude oil in a tank under different initial particle sizes and different continuous-phase viscosities. The results indicate that the maximum error in the comparison of the water content changes at different positions in the sedimentation cylinder after 1 h with experimental values is approximately 8.34%, confirming the precision of the developed settling model. When the initial particle size of liquid droplets in the tank increases from 8 μm to 64 μm, the maximum water content in the tank increases by 1.115%, and the magnitude of the increase in the average droplet size decreases by 90%. As the viscosity of the oil increases (from 35.26 mPa · s to 77.77 mPa · s), the maximum water content in the tank decreases by 1.331%, while the height of the stable water content region increases by 13.2%.

Exploring the Dissemination and Development of Culture: The Protection and Inheritance of Glove Puppetry

As a traditional folk art form originating from Fujian Province, China, and included in the Intangible Cultural Heritage List, glove puppetry has a profound historical background and rich and unique cultural connotations. With the promotion of globalization and the information age, its scope of dissemination has spread to Taiwan and even to Southeast Asia, gradually attracting widespread international attention. However, such traditional art is facing many challenges in today’s society, such as cultural shock, talent loss, and adaptability. To better deal with these problems, this study will focus on the historical evolution and development of glove puppetry, its current status, and solutions, aiming to provide theoretical support and case references for its sustainable development in the context of globalization and continuously create a relatively good ecological environment for glove puppetry. The specific methods include reviewing historical documents, reading relevant field survey data, and analyzing the implementation and impact of solution strategies. The research results show that glove puppetry has undergone large and small dissemination transformations in the course of historical evolution, but in today’s information society, it still faces problems such as insufficient traditional protection, talent loss, and poor cultural adaptability. To meet these challenges, the study mentioned solutions that have already been implemented. The research concluded that the continued development of glove puppetry depends on the protection and inheritance of traditional art forms. These findings have created a good cultural ecology for the survival and development of glove puppetry in modern society and provided valuable references and practical direction.

Benefit evaluation of sloping land conversion program in the upper reaches of the Yellow River

This study used forestry statistical data and field survey data from 2000 to 2018 to analyze the ecological restoration effect of the returning farmland to forest project in the upper reaches of the Yellow River, considering four perspectives, namely, project construction goals, ecosystem quality, ecosystem service functions, and ecological restoration driving factors. One-way ANOVA and logit regression analysis methods were used for comparison. The results show that the implementation of the Grain for Green Project has reduced the carrying capacity of rural land, effectively curbed the continuous deterioration of the ecological environment, and protected and benefited the forest ecosystem. (1) Initiatives of the return farmland to forest project have achieved the expected goals, and the forest coverage rate has increased significantly from 5.26 % (in 2000) to 15.63 % (in 2019); the proportion of primary, secondary, and tertiary industries related to forestry has reached a reasonable level, and the economic benefits thereof continue to improve. (2) Indicators such as total forest and grass vegetation coverage, vegetation net primary productivity, and forest and grass health index reflect that the functional quality of the regional forest and grass ecosystem is gradually improving. (3) The ecosystem service function of the project region has improved considerably, and the ecological benefits are significant. (4) In terms of the contribution value of the driving forces for this ecological restoration project, they can be ranked as follows: government investment > reducing land carrying capacity > policy of returning farmland to forest > government management > hydrological factors > meteorological factors. (5) After the implementation of the Grain for Green Project, farmers' income has increased significantly, but the changes in livelihood capital income are not synchronized. As the ecological environment in the Grain for Green project areas gradually improved from deterioration, the natural capital and social capital of farmers' livelihood capital decreased significantly, while the physical capital and financial capital increased significantly, with no significant change in human capital. Farmers' satisfaction with the Grain for Green Project is as follows: natural capital has a significant negative impact, while financial capital and social capital have significant positive impacts, and there are no significant changes in physical capital and human capital. Finally, the consistency test results show that the fit is as high as 95 %, and the accuracy exceeds 90 %. Notably, the implementation of the Grain for Green Project has played a pivotal role in ecological restoration and contributed greatly to ecological benefits. These achievements provide a scientific basis and theoretical support for the country to formulate relevant policies for forestry projects, which holds great significance for the country in addressing the contradiction between economic and social development and ecological protection.

Characteristics, impacts and future research directions of Mongolian peatlands

Mongolia is an important peatland distribution area in the world. Over the past few decades, Mongolian peatlands have undergone significant degradation due to climate change and human activities, yet there remains substantial uncertainty about the impacts of Mongolian peatland changes on regional environment and human society. Here, compiling the data of peatland distribution, climate, human activity, as well as the permafrost, we systematically review the distribution, changes, and the ecosystem service values of the Mongolian peatlands in the face of climate warming and intensifying human activities. The current data show that the total area of peatland in the Mongolian is 15500~27000 km2, and most of the peatlands are distributed in permafrost regions, while the accuracies of these maps were not assessed. In addition to climate warming, overgrazing, mining activities, and transportation, we suggest permafrost degradation also poses significant threatens on the peatlands. Although the importance of Mongolian peatlands has been recognized, the ecosystem service values, including water provision, habitat quality, carbon fixation, soil conservation, and wind erosion prevention largely remain unknown. Currently, efforts have been made to protect the Mongolian grassland, but there are no specific measures to combat peatland degradation. To better understand the changes and roles of peatland ecosystems in regulating regional development, we propose three research directions for future studies: 1) produce a detailed map of peatland distribution based on field survey data, new remote sensing data, and new algorithms; 2) Unveil the mechanisms underlying the interaction of peat, vegetation, and permafrost; 3) Evaluate the ecosystem services of Mongolian peatlands. These knowledges are the scientific foundation to propose and implement measures to protect, maintain, and sustainably utilize peatlands in Mongolia.

Urbanization Rapidity and Its Impact on Shuklagandaki Municipality

This study examines the trends and causes of urbanization as well as how they affect Nepal's Shuklagandaki Municipality, which is urbanizing quickly. Using a mixed-methods approach, the study incorporates data from both qualitative and quantitative sources. Quantitative information was gathered from field survey and qualitative data were collected from public reports, census records, and government statistics to examine demographic and economic developments in the municipality during the previous 20 years. Through in-depth interviews with important stakeholders, such as public servants, company owners, and community leaders, qualitative data were acquired. Regression analysis and other descriptive and inferential statistics were used in the data analysis process. The results show that throughout the past 20 years, Shuklagandaki Municipality has had notable increase in both demographic and economic metrics. Urban expansion was primarily driven by population increase and economic development; infrastructural improvements, while significant, were secondary. The necessity for planning and policy initiatives that support sustainable growth while attending to the needs and well-being of present and future inhabitants is highlighted by the difficulties and possibilities brought about by the fast urbanization. The article finishes with a summary of the key results, a discussion of the research limitations, and references for future research topics to fill in the gaps in the body of knowledge and address unresolved issues with urban expansion in Shuklagandaki Municipality.

Spatiotemporal prediction of greenhouse gas emissions from rubber wood industry, taking Hainan as the case

The rubber wood furniture industry chain, including planting and manufacturing subsystems, emits significant greenhouse gases (GHGs), meanwhile, has huge carbon emission reduction potential. However, quite few studies have taken the whole industry chain GHGs into consideration, especially assessing and predicting those from rubber tree planting to furniture manufacturing. We took the rubber wood furniture of Hainan province as the case, explored its whole life cycle GHGs from cradle-to-gate and predicted the potential GHGs from 2031 to 2062. This study is fully based on field survey and sampling data, including that of the rubber tree planting (40-year cycle) and furniture manufacturing. The results reveal: (1) Whole industry chain of rubber wood furniture emits 3.27 × 106 kgCO2-eq GHGs per 20,000 t rubber logs consuming, where the planting accounts the most (88.20%). Transport and electricity consumption are the main GHGs sources of planting and manufacturing subsystems respectively; (2) The whole life-cycle GHGs of rubber wood furniture in 2023 of Hainan is 2.07 × 107 kgCO2-eq, which mainly come from Danzhou (24.74%), Haikou (19.55%), and Qiongzhong (15.79%); (3) The total GHGs from the rubber wood furniture industry in Hainan from 2031 to 2062 are 210 MtCO2-eq and 129 MtCO2-eq respectively, without or with felling restriction. The changes of GHGs from 2051 to 2062 are caused by the regional center shift of planting gravity; (4) Improving energy use efficiency and optimizing the location of furniture factories would reduce GHGs. This study can provide empirical support for the low carbon sustainable transformation of the rubber wood furniture industry worldwide.

A Study on Revenue Distribution of Chinese Agricultural E-Commerce Supply Chain Based on the Modified Shapley Value Method

With the rapid development of e-commerce in China, “live broadcast + e-commerce” has become an emerging mode of the e-commerce industry. The speedy growth of the digital economy has also provided a favorable external environment for fresh agricultural products to ride on the e-commerce express train. As a result, more and more suppliers of fresh agricultural products choose to sell their products on e-commerce platforms and conduct live streaming. This paper utilizes the e-commerce supply chain field survey data, takes tomato as the specific analyzed variety, and studies the revenue distribution pattern of each subject in the supply chain. The purpose of this paper is to explore the optimization strategy of the revenue distribution of an agricultural e-commerce supply chain, and the results show that the agricultural e-commerce supply chain effectively promotes the matching of supply and demand of medium- and high-end agricultural products, realizes the quality premium of medium- and high-end agricultural products, and significantly improves the overall revenue level of the supply chain. The field survey found that under the supply chain model of “farmers + cooperatives + e-commerce platform”, farmers, cooperatives, and e-commerce platforms gained $2865, $3098, and $1111, respectively, for operating one mu of tomatoes in a year. According to the traditional Shapley value method, from the point of view of the contribution to the cooperative income, part of the income of the farmers and cooperatives should be compensated to the e-commerce platform, and the specific results are as follows: the income of the farmers should be reduced from $2865 to $2729, the income of the cooperatives should be reduced from $3099 to $2955, and the income of the e-commerce platform should be increased from $1111 to $1390. According to the Shapley value method based on the risk coefficient correction, from the perspective of risk compensation, part of the earnings of the e-commerce platform should be compensated to farmers and cooperatives, so as to establish a more equitable and reasonable pattern of earnings distribution, with the specific results: the earnings of farmers should be increased to $3205, the earnings of cooperatives should be increased to $3148, and the earnings of the e-commerce platform should be reduced to $722.

A Typical of Tsunami Generation Caused by Volcano Flank Collapse in Banda Neira, Maluku, Indonesia

Abstract The history eruption of the Banda volcanoes was recorded in 1632, 1816, and 1988 and was preceded by significant earthquakes. In the eruption in 2017, there were 28 volcanic earthquakes, indicating a rock cracking process due to the movement of magma in the form of gas, liquid, and rock solids. We suspect that when the earthquake occurs, the rock-cracking process upon the eruption will potentially trigger the volcano flank to collapse into the sea and generate a tsunami in the Banda Naira and surrounding area. We contribute to modeling the travel time and tsunami inundation resulting from the flank collapse of Banda Volcano. BATNAS bathymetry data is used to run tsunami simulations. We use aerial photography from field survey data to interpret Banda Volcano failure parameters, including diameter, direction of sliding of the collapse, and slope of the collapse of the side of the Banda Volcano. Based on the tsunami simulation, the volcano flank collapse source on Banda Volcano produced a maximum tsunami in Banda Naira as high as 6.2 meters, and the tsunami will arrive around 6 – 8 minutes. While in AI Island, tsunami inundation reached 55.87 m and arrived in 4 minutes. Meanwhile, the maximum elevation of Banda Naira Island is 3.5 meters, with a population of 21,000 people in March 2024. Tsunami inundation has the potential to submerge entire residential areas in Banda Neira.

Has Cross-City Commuting Promoted Housing Purchases among the Workforce within Metropolitan Areas?—An Empirical Analysis from Micro Survey Data from China’s Three Major Metropolitan Areas

The ability of the cross-city commuting labor force to obtain housing has a profound impact on the development of the housing market and the enhancement of social welfare, but whether cross-city commuting has facilitated housing purchases remains to be verified However, the research on whether cross-city commuting behavior promotes labor force housing purchase in metropolitan areas is still lacking, especially in China, where the culture of buying houses is relatively special. This article used field survey data from the 2023 China Metropolitan Area Occupation and Housing Status Sampling Survey to empirically analyze whether cross-city commuting has facilitated housing purchases within metropolitan areas. The analysis was conducted by constructing a baseline model, a mediation effect model, and a subsample regression model. The results show that the cross-city commuting facilitated housing purchase within metropolitan areas, and the location preference is to purchase a house with a distance of 20–40 km from the workplace, but the contribution of the cross-city commuting to multi-suite purchases is relatively low. Mechanism analysis shows that compared to the workers who work and live in peripheral areas or the workers who work and live in cores, intercity commuters are promoted to purchase housing by relatively higher income and inducement of the housing price gap. The above conclusions still hold after controlling potential endogeneity issues and in robustness tests. The research of this paper can provide a new perspective for alleviating the housing inequality in the metropolitan area.

Analysis of organic matter stock dynamics in arable soils of Yamal: simulation experiments with the ROMUL model

The goal of this work is to analyze the dynamics of soil organic matter (SOM) in arable soils of Yamal using computational experiments with the ROMUL model. Soil temperature and moisture dynamics were simulated using the SCLISS model. The Yamal experimental station was organized in 1932. The soil is Plaggic Podzol. The thickness of humus horizon (PY) is 30 cm. Pools, kg/m2: SOM – 9.32 and 13.75; N – 0.46 and 0.66 for 0–20 and 0–30 cm respectively. Background: soddy-green-moss tundra near Salekhard. Soil: Folic Podzol: litter (O, 2 cm) and humus-accumulative (AY, 4 cm) and illuvial ferruginous (BF, 6 cm) horizons. Pools, kg/m2: SOM – 1.38 and 2.69, N – 0.03 and 0.18 for 0–2 and 2–6 cm respectively. The quantity and quality of background fall was estimated according to literature data. Clarification of the amount of fall was carried out by the method of inverse problem solving (spin-up). Peat application was simulated: starting application in the dose of 12 kg/m2 and maintenance (every 6 years) in doses 4, 8 and 12 kg/m2, N 1%. Application of mineral fertilizers, 2 variants: a) N 4 g/m2 (40 kg/ha) in peatting years and b) application of the same dose of nitrogen every year. The duration of computational experiments is 30 and 90 years. Computational experiments showed that after the starting peatting of Folic Podzol at the rate of 12 kg/m2 after 30 years, only 15% of the applied detritus remained. Maintenance peatting of 8–12 kg/m2 leads to an increase in SOM pool to 20–30 kg/m2 and excessive accumulation of detritus. Application of 4 kg/m2 of peat once every 6 years for 90 years shows the dynamics of SOM pools from Folic Podzol to Plaggic Podzol which is confirmed by field survey data. Application of mineral nitrogen (4 g/m2) once every 6 years does not affect SOM pools. Annual application of mineral N (4 g/m2) increases SOM pools due to intensified humification. This fact requires experimental verification.

Exploring the influence of workplace environment on job performance: a socio-cognitive perspective

This study investigates the evolution of job performance from socio-cognitive and knowledge-based perspectives, focusing on key perceived environmental factors. The research model proposed posits that perceived diversity and procedural justice positively affect job performance through the mediation of job self-efficacy and work engagement. Additionally, knowledge-oriented leadership is examined as a moderator influencing the formation of job self-efficacy and work engagement. Empirical testing of these hypotheses was conducted using field survey data collected from working professionals in a prominent computer and communication firm within the high-tech industry. The findings not only have theoretical and practical implications but also acknowledge certain limitations inherent in the research. Specifically, a limitation of this study is that it surveyed professionals in technology companies, so caution is advised when extending its implications to employees in non-tech sectors.

Principle, structure and application progress of the forest landscape model FireBGCv2.

Forest landscape model can quantitatively simulate the spatiotemporal variations in forest structure and function at the landscape scale based on traditional field survey data and mathematical models, providing a reference for the formulation of scientific forest management strategies. FireBGCv2 is one of the representative models currently used in the research area of forest landscape changes. It can simulate ecological processes at various scales, including trees scale (tree growth, establishment, and mortality), stand scale (carbon and nitrogen pools, fuel treatment, decomposition), site scale (resource competition and species phenology), and landscape scale (seed dispersal and wildfire disturbances), and the effects of those processes on forest landscape structure and function. The advantage of this model lies in its ability to simulate multiple ecological processes while considering the diversity and complexity of ecosystems. However, it also has drawbacks, such as high computational demands and complexity of use. We summarized the basic principles and structure of FireBGCv2 and introduced its application progress in forest landscape research and management. Currently, the application of the FireBGCv2 model, both domestically and internationally, mainly focused on exploring the interactions between fire, climate, and vegetation, quantifying the spatial and temporal dynamics of fires, and describing potential fire dynamics under future climate scenarios and land management strategies. With the in-depth development of forest landscape model theories and applications, the future prospects of FireBGCv2 include improving and updating the model's algorithms, adding new functional modules to explore fire management issues, and meeting the needs of different users.

Impact of Ecological Cognitive Bias on Pesticide Reduction by Natural Rubber Farmers in China: Insight from Price Insurance Satisfaction

Some natural rubber farmers mistakenly equate the ecological functions of rubber plantations with those of primary forests. This cognitive bias can hinder pesticide reduction efforts. Meanwhile, natural rubber farmers gain security through price insurance, which helps them adopt a long-term perspective on environmental protection, mitigating the negative impact of cognitive biases on pesticide use decisions. However, existing research often overlooks the influence of ecological cognitive bias on pesticide reduction and the moderating role of price insurance satisfaction. This study utilizes field survey data from Hainan and employs logit models and double machine learning models to empirically analyze the impact of ecological cognitive bias on pesticide reduction among natural rubber farmers. It further tests the underlying mechanisms using moderation models. The results indicate that (1) ecological cognitive bias negatively affects pesticide reduction among natural rubber farmers, and (2) price insurance satisfaction mitigates the impact of ecological cognitive bias on pesticide reduction. Based on these findings, the government should enhance education and training to raise ecological awareness among natural rubber farmers and reduce ecological cognitive biases. Disseminating knowledge about price insurance and establishing a comprehensive insurance system can secure farmers’ income and promote the rational use of pesticides.

Occurrence of biennial sporophytes of the kelp Saccharina japonica in Hokkaido, Japan

Recent studies suggest that relict communities of Saccharina japonica var. ochotensis are rarely observed in southwestern Hokkaido, where S. japonica. var. religiosa is generally distributed. Previous research has mainly focused on the morphology of these species, and field survey data is very limited. In the present study, relict S. japonica var. ochotensis communities were observed only near the estuaries of larger rivers, specifically in estuarine areas where bedrock is present and the seashore has a gentle gradient slope. The biomass and size (length, width, and weight) of annual and biennial relict S. japonica. var. ochotensis were recorded. The carbon/nitrogen ratio of the kelp sporophytes was analyzed, and relatively lower values were observed in the relict community of this species. This information may help in the maintenance of kelp beds in southwestern Hokkaido and the wise utilization of relict S. japonica var. ochotensis in the estuarine areas of southwestern Hokkaido, Sea of Japan.