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The Pacific Crest Trail (PCT) is a National Scenic Trail that extends approximately 2,653 miles from the border of California and Mexico to the border of Washington State and Canada. This study examined land management and hiker issues that day, overnight, and thru-hikers experience in California while navigating the PCT in order to inform land managers. This quantitative survey, completed through Qualtrics, was disseminated to thru-hikers who completed the trail between 2017 and 2021, and individuals who used the trail for shorter durations. Survey questions focused on technology, Trail Angels, rule enforcement by land management agencies, the permitting process by the Pacific Crest Trail Association (PCTA), hiker education, and hiker demographics. Descriptive statistics were calculated and analyzed. Results indicate that most hikers prefer articles on the PCTA website, Leave No Trace (LNT) website, and certifications to gain education about the trail. They also felt that personal contacts were the most effective way to gain pre-trip education. Almost all hikers use technology on the trail, such as navigation or informational apps, emergency calls, taking photos, and listening to videos or music. More thru-hikers rely on navigational apps than day/overnight users. Many hikers felt there should be more rangers in the backcountry but also felt that social enforcement of rules is effective. Regarding Trail Angels, thru-hikers felt they were important for transportation, food/water, and shelter. Managerial implications for public land managers included a need to develop ways to educate users. This can be done in-person, online, or through signage. Increasing the presence of rangers or volunteers on the trail was also recommended, as well as developing area or jurisdiction-specific apps for information and education about trail conditions or rules. Additional education of sustainable hiking behaviors may help mitigate potential negative impacts hikers may have on the environment. Land managers must continue to assess what is currently being done and reevaluate on an ongoing basis in order to preserve and maintain sustainable use of public lands.

This study investigates the impact of anthropogenic land use on the body size of bees across 18 different species. Adult bee body size, primarily influenced by developmental nutrition, is significantly affected by the availability of floral resources. Developed land often has reduced floral diversity and density is hypothesized to produce smaller bees due to limited food resources. Specimens from the UCSB Invertebrate Zoology Collection were categorized based on their collection sites into three land use types: developed, agricultural, and forest using USGS National Land Cover Database. Measurements of head width, intertegular distance (ITD), and dry mass were taken to assess body size. A body size index was calculated as the average of these measurements. Analysis of Variance (ANOVA) were done in Python version 3.12.4. Results indicate that bees from agricultural habitats are significantly larger than those from developed and forest habitats across all metrics (head width, ITD, dry mass, and body size index). These findings highlight the influence of landscape changes on bee functional traits, providing essential insights into the ecological consequences of land use on bee health.This poster was presented at the UCSB CSEP summer colloquium 2024.

This report aims to investigate the community engagement process so planners can more effectively work with communities and reckon with the historical trauma caused by planners in the past. Planning as an industry is responsible for the forceful removal of communities under the name of “urban decay” and is a direct cause of why some communities remain impoverished today. This history has not been long forgotten; it continues to live on in the communities directly affected, and trust when working with public agencies is low. Public agencies must understand this trauma as they work with these communities to build a better future. This report chronicles the Little Tokyo/Arts District Station joint development process by interviewing Little Tokyo residents and other stakeholders involved with the process and examining archival documents. While relatively small, Little Tokyo has a long history of asserting its autonomy in community development issues. I highlight the history of community-based organization and planning that has sustained Little Tokyo into the community it remains today. Through my findings, I recommend a history-informed planning process among public agencies. A holistic approach to planning must be taken that considers the community context in historical and contemporary terms. While the process of community engagement can be long and expensive, it is a way for public agencies to repair their relationship with communities that have been wronged in the past.

Stabilizing climate requires reducing greenhouse gas (GHG) emissions and storing atmospheric carbon dioxide (CO2) in land or ocean systems. Soil management practices can reduce GHG emissions or sequester atmospheric CO2 into inorganic and organic forms. However, whether soil carbon strategies represent a viable and impactful climate mitigation pathway is uncertain. A specific question concerns the role that land-management practices and soil amendments can play in realizing California’s ambition for carbon neutrality by 2045. Here we examine the carbon flux impacts of soil conservation (i.e., compost, reduced tillage, cover crop) and enhanced silicate rock weathering (EW) practices at different areal extents of implementation in cropland, grassland, and savanna in California under two climate change cases. We show that with implementation areas of 15% or 50% of private cultivated land, grassland, and savanna in California, soil conservation practices alone can contribute 1.4 0.7 2.1 % ( − 1.8 − 0.9 − 2.7 Mt CO2eq y−1) and 4.6 2.3 6.9 % ( − 6.0 − 3.0 − 8.9 Mt CO2eq y−1) of the additional emissions reduction needed (beyond previous targets) to meet the 2045 net neutrality goal (−129.3 Mt CO2eq y−1), respectively, on an average annual basis, including climate uncertainty. Including EW in these scenarios increases the total contributions of management practices to 4.1 2.5 5.6 % ( − 5.2 − 3.2 − 7.3 Mt CO2eq y−1) and 13.5 8.2 18.6 % ( − 17.5 − 10.7 − 24.2 Mt CO2eq y−1), respectively, of this reduction. This highlights that the extent of implementation area is a major factor in determining benefits and that EW has the potential to make a real contribution to net reduction targets. Results are similar across climate cases, indicating that contemporary field data can be used to make future projections. With EW there remains mechanistic uncertainties, however, such as rock dissolution rate and environmental controls on weathering products, which require additional field research to improve understanding of the technological efficacy of this approach for California’s 2045 carbon neutrality goal.

Economists tend to favour price-based approaches, such as gasoline and carbon taxes, to address the negative impacts of car travel, while urban planners tend to emphasise land use planning such as compact development. In this paper, we argue that the two approaches are synergistic. We use precinct-level data from two California referenda to show that land use planning makes pricing more feasible: voters in dense, transit-oriented neighbourhoods are more willing to support a carbon price and increased gasoline taxes. Political ideology is a more important determinant of voting patterns, but in a closely divided election, land use patterns, public transportation, and other aspects of the built environment can determine the success of a referendum on driving taxes. Our results also imply that the voluminous research on land use and transportation underestimates the long-run impacts of compact development on driving, through ignoring the ways in which urban form shapes the politics of taxation.

Senate Bill (SB) 743 (2013) and its related regulations eliminated automobile level of service (LOS) and replaced it with vehicle miles traveled (VMT) as the primary transportation impact metric for land development projects under the California Environmental Quality Act. Actual implementation of the LOS-to-VMT shift was left up to lead agencies, primarily local governments. The LOS-to-VMT shift was expected to create many challenges, given the often-limited resources of local governments, the entrenched use of LOS, and the perceived lack of established practice regarding VMT estimation, mitigation, and monitoring. With those concerns in mind, researchers at the University of California, Davis investigated how local governments have been implementing the LOS-to-VMT shift for land development projects.  This policy brief summarizes the findings from that investigation. View the NCST Project Webpage

Estimates of the land area occupied by wind energy differ by orders of magnitude due to data scarcity and inconsistent methodology. We developed a method that combines machine learning-based imagery analysis and geographic information systems and examined the land area of 318 wind farms (15,871 turbines) in the U.S. portion of the Western Interconnection. We found that prior land use and human modification in the project area are critical for land-use efficiency and land transformation of wind projects. Projects developed in areas with little human modification have a land-use efficiency of 63.8 ± 8.9 W/m2 (mean ±95% confidence interval) and a land transformation of 0.24 ± 0.07 m2/MWh, while values for projects in areas with high human modification are 447 ± 49.4 W/m2 and 0.05 ± 0.01 m2/MWh, respectively. We show that land resources for wind can be quantified consistently with our replicable method, a method that obviates >99% of the workload using machine learning. To quantify the peripheral impact of a turbine, buffered geometry can be used as a proxy for measuring land resources and metrics when a large enough impact radius is assumed (e.g., >4 times the rotor diameter). Our analysis provides a necessary first step toward regionalized impact assessment and improved comparisons of energy alternatives.

Many methods exist for engaging experts in interactive groups to explore, clarify, and/or decide on various issues. In an investigation of four possible future scenarios concerning transportation and land use in California, we developed a novel “hybrid policy Delphi” method for use with a panel of 18 experts. We applied it to explore the policies and practices that would likely lead to each of the four scenarios and the consequences that would result from them. Through our process, panel members discussed and reflected on the scenarios in multiple ways. The scenario they considered most desirable they also deemed least likely to occur, and they foresaw the likely trajectory of California transportation and land use leading to less desirable scenarios. Our mix of discussion and questionnaires traded the benefit of anonymity for the benefit of exploratory, interactive discussion. In addition, our use of surveys before and after meetings allowed us to track changes in panel opinion on a central question and discuss the survey results at meetings, at the cost of greater administrative effort. We discuss the results of this hybrid policy Delphi approach, reflect on how it worked, and conclude with a discussion of limitations and future directions.

China has committed to achieve net carbon neutrality by 2060 to combat global climate change, which will require unprecedented deployment of negative emissions technologies, renewable energies (RE), and complementary infrastructure. At terawatt-scale deployment, land use limitations interact with operational and economic features of power systems. To address this, we developed a spatially resolved resource assessment and power systems planning optimization that models a full year of power system operations, sub-provincial RE siting criteria, and transmission connections. Our modeling results show that wind and solar must be expanded to 2,000 to 3,900 GW each, with one plausible pathway leading to 300 GW/yr combined annual additions in 2046 to 2060, a three-fold increase from today. Over 80% of solar and 55% of wind is constructed within 100 km of major load centers when accounting for current policies regarding land use. Large-scale low-carbon systems must balance key trade-offs in land use, RE resource quality, grid integration, and costs. Under more restrictive RE siting policies, at least 740 GW of distributed solar would become economically feasible in regions with high demand, where utility-scale deployment is limited by competition with agricultural land. Effective planning and policy formulation are necessary to achieve Chinas climate goals.

Climate change intensifies longstanding tensions over groundwater sustainability and equity of access among users. Though private land ownership is a primary mechanism for accessing groundwater in many regions, few studies have systematically examined the extent to which farmland markets transform groundwater access patterns over time. This study begins to fill this gap by examining farmland transactions overlying groundwater from 2003-17 in California. We construct a novel dataset that downscales well construction behavior to the parcel level, and we use it to characterize changes in groundwater access patterns by buyer type on newly transacted parcels in the San Joaquin Valley groundwater basin during the 2011-17 drought. Our results demonstrate large-scale transitions in farmland ownership, with 21.1% of overlying agricultural acreage statewide sold at least once during the study period and with the highest rates of turnover occurring in critically overdrafted basins. By 2017, annual individual farmland acquisitions had halved, while acquisitions by limited liability companies increased to one-third of all overlying acres purchased. Together, these trends signal increasing corporate farmland acquisitions; new corporate farmland owners are associated with the construction, on comparable parcels, of agricultural wells 77-81 feet deeper than those drilled by new individual landowners. We discuss the implications of our findings for near-term governance of groundwater, and their relevance for understanding structural inequities in exposure to future groundwater level declines.

Strawberries in California are grown in specific coastal areas where land is scarce and climate change threatens future production. Strawberry growers are under pressure to adopt sustainable production strategies such as crop rotation, but this practice requires more land than back-to-back planting. The objectives of this research were to quantify the rate of crop rotation across the three main strawberry producing regions in California (Ventura, Santa Maria, and Monterey Bay), and evaluate geographic and edaphic influences on crop rotation. All strawberry fields in the main strawberry producing regions of California were identified by satellite imagery and manual inspection for the years 2017 through 2022. ArcGIS Pro was used to outline each strawberry field and compare among years to determine the period between successive strawberry plantings. Edaphic characteristics and shapefiles for surrounding fields were retrieved from public datasets. The three regions significantly differed in their rates of crop rotation. On average, 95, 52, and 25% of strawberry hectares were rotated each year in the Monterey Bay, Santa Maria, and Ventura regions, respectively. Shorter rotation lengths were associated with reduced distance from the ocean and soil with a higher percentage of sand. Based on 2 years of disease surveys, fields infested with Macrophomina phaseolina tended to be further inland than fields infested with Fusarium oxysporum f. sp. fragariae in the Monterey Bay region. This study determined that distance from the ocean and soil texture are associated with crop rotation lengths in California strawberry production. Enough land may be available in the Santa Maria and Monterey Bay regions for growers to lengthen crop rotations, but water quality, social networks, and financial considerations that were outside the scope of this study are likely to limit the ability for strawberry growers to maximize the duration of crop rotations.

[Display omitted] • Introducing new combined models of MC-MCE-CA, MC-MLP-CA, MC-SW-CA and MC-LR-CA for the development of land use methodology, with emphasizing the nature and principles of them for modeling of land use changes studies. • Comparing the capabilities of the new models with the traditional CA-Markov model in terms of the overall accuracy of the models and the basis of their implementation in land use change studies. • Monitoring and modeling of land use changes from the areas of industrial and agricultural activities in a long time range of about half a century (1989-2037). Land use change is one of the most significant environmental issues in many countries and is the main reason for ecosystem changes. This issue is one of the most important environmental crises in Iran due to the lack of planning and inappropriate human use of the natural environment. Many parts of Iran, especially the Urmia Lake basin, are involved in challenging land use changes. The trend of land use changes extracted from Landsat images in the Urmia lake basin with overall accuracy and Kappa coefficient of more than 85 % and 80 % respectively shows that during the 32-year period (1989–2021) agricultural lands, built-up lands and barren lands respectively 3330.83 km2, 466.86 km2 and 5325.8 km2 have increased in area. On the other hand, the areas of vegetation and water bodies decreased by 6625.79 km2 and 2497.7 km2, respectively. The current trend of land use changes in Urmia basin based on all models of Markov chain-Multi Criteria Evolution-Cellular Automata (MC-MCE-CA), Markov Chain-Multilayer Perceptron-Cellular Automata (MC-MLP-CA), Markov Chain-Sim Weight-Cellular Automata (MC-SW-CA), Markov Chain–Logistic Regression-Cellular Automata (MC-LR-CA) indicate the continuation of changes until 2037. Meanwhile, based on the most accurate models such as MC-MLP-CA and MC-LR-CA models, agricultural lands will increase by 1436.60 km2 and 1258.33 km2, built-up lands by 75.23 km2 and 65.52 km2, and barren lands by 808.94 km2 and 856.90 km2 respectively. Also, the vegetation lands will be reduced by 1890.64 km2 and 1755.31 km2 and water bodies by 430.13 km2 and 425.44 km2. In general, the results showed that MC-MLP-CA, MC-LR-CA, MC-SW-CA, MC-MCE-CA models with Overall Kappa 89.89, 87.09, 84.52 % and 84.84 and Percent of Correctness 93.65, 93.09, 91.52 and 91.77 respectively, with higher accuracy than the CA-Markov model (Overall Kappa = 81.49 % and Percent of Correctness = 87.49 %) are more effective for land use changes modeling. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the response of ecosystem service value to land use change and predicting future trends, and to provide scientific reference for land use pattern planning in the arsenic sandstone area. [Methods] Based on the remote sensing images of the four phases of sandstone area from 2000 to 2020, the change characteristics of LUCC and ESV in the past 20 years were analyzed based on GIS technology and ESV evaluation methods. The response of LUCC induced by ESV was revealed. The development trend of LUCC and ESV was predicted by using Markov model. [Results] (1) In 2000- 2020, the total area of LUCC remained unchanged, and the increase of construction land was the most obvious, with a total increase of 762.73 km² and a growth rate of 4.57%. The grassland decreased by 548.79 km² in total, with a reduction rate of 3.28%. (2) The overall level of ESV showed a downward trend, from 19 949.65 million yuan to 18 997.19 million yuan, a decrease of 4.78%, of which grassland ESV changed the most, decreasing by 746.29 million yuan, accounting for 78.35% of the overall decline rate. (3) ESV was positively correlated with the changes in grassland, woodland, cultivated land, water area and construction land, and negatively correlated with unused land. (4) It is predicted that the area of cultivated land, forest land, grassland and water area will decrease to 96.69%, 98.94%, 94.27% and 99.12% of those in 2020 in the next 10 years. Construction land and unused land will increase to 150.03% and 121.61%, and the overall ESV level in sandstone area will continue to decrease to 92.81%. [Conclusion] The areas of cultivated land, forest land, grassland, and water are decreasing, while the area of construction land and unused land will increase. ESV will continue to decrease, and there is a linear relationship between ESV changes and land use changes. In the future, the area of construction land will increase, and ESV will continue to decrease. Reasonably adjusting the area of construction land is beneficial for ecological construction and vegetation restoration and reconstruction in the sandstone area of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the spatial and temporal evolution patterns of vegetation cover in the urban agglomeration of southern Sichuan, to analyze its driving mechanism, and to provide reference and decision-making basis for promoting ecological environmental protection and sustainable socioeconomic development in the upper reaches of the Yangtze River. [Methods] The vegetation cover was taken as the research object. The coefficient of variation and linear regression research methods were used to analyze the spatial and temporal evolution characteristics of the vegetation change in the urban agglomeration of south Sichuan from 2001 to 2021, and the geographic detector model was used to explore the influencing factors. [Results] (1) The overall condition of vegetation cover in the south Sichuan urban agglomeration was good, and the proportion of areas with vegetation cover of 0.4 or more was 71.74%. The change of vegetation cover was dominated by low fluctuation, accounting for 78.16%. The trend of vegetation degradation was significant, accounting for 8.89%. (2) The degree of influence of each driving factor on vegetation cover was ranked in descending order: elevation> land use type average annual temperature> slope population density > GDP > urbanization rate average annual evaporation average annual precipitation aspect. Among them, the explanatory power q-values of the first six factors were all greater than 16%, which were the main driving factors affecting the change of vegetation cover. (3) Any two-factor interactions were dominated by two-factor enhancement and nonlinear enhancement, in which the q value of the interaction between elevation and land use type was the largest, 0.369. (4) When the elevation was 1 200 to 1 400 m, the mean annual temperature was 12.15 to 15.16 °C, the slopes were 32° to 35°, the population density was less than 22.31 people/km², the GDP was 122 to 1 221 yuan/km2 and when the land use type was woodland, the vegetation was most suitable. [Conclusion] The overall condition of vegetation cover in the south Sichuan urban agglomeration from 2001 to 2021 was good, and topography, meteorological conditions and socioeconomic factors all had a significant impact on regional vegetation changes. [ABSTRACT FROM AUTHOR]

[Objective] The aim of this study is to explore the accuracy and applicability of different machine learning models for predicting the spatial distribution of surface soil organic carbon density (SOCD) with limited samples, which can provide a references for the study of watershed scale carbon pool in the Chinese Loess Plateau. [Methods] In this study, we compared the accuracy and stability of the predicted SOCD in topsoil (0-20 cm) by four machine learning models, namely Multiple Linear Stepwise Regression (SR), Random Forest (RF), Extreme Gradient Boosting (XGB) and Support Vector Machine (SVM), based on the limited measured samples in a sub-watershed of Yanhe River in the Chinese Loess Plateau. [Results] (1) Under the condition of limited samples, all models successfully and appropriately predicte the spatial distribution of SOCD, among which the SVM model has the best model performance, and the average RMSE, R² and MAE of 50 predictions is 0.74. 0.43 and 0.64, respectively. (2) The average SOCD of different land use types are consistent between measured and predicted values but shows significant difference among land use types. SOCD decreases in the order: shrubland forestland > grassland > cropland. The total organic carbon of cultivated land in the study area is 2.39×106t (0-20 cm). (3) The evaluation of feature importance shows that terrain factors, NDVI max, near-infrared surface reflectance (B5) and Brightness index have significant contributions to the accuracy of predictions. [Conclusion] Under the condition of limited samples, the machine learning model combined with controlling features can be effectively applied to the prediction of the spatial distribution of topsoil SOCD at the watershed scale in the Chinese Loess Plateau. [ABSTRACT FROM AUTHOR]

[Objective] Habitat quality is the potential of ecosystems to provide the necessary conditions for species survival and reproduction, and is the key to improving ecosystem functions. Studying the habitat quality of the Yangtze River Basin is of great significance for national major strategies such as green development of the Yangtze River Economic Belt and the protection of the Yangtze River. [Methods] Based on land use data from 1980 to 2018 in the middle and lower reaches of the Yangtze River, the InVEST model was used to study the spatiotemporal changes in land use change, habitat quality, and habitat degradation in the middle and lower reaches of the Yangtze River from 1980 to 2018. [Results] (1) As the main type of land use in the study area, woodland was decreasing, mainly turning to construction land and water area, which greatly reflected the driving effect of population growth, economic development and environmental protection on the change of land use structure. (2) The overall habitat quality of the study area was at a high level. showing a trend of low in the east and middle, and high in the south, which was consistent with the land use pattern that most of the cities along the Yangtze River in the east and middle of the study area were dominated by construction land, and the south was dominated by woodland and grassland. (3) In the study area, the degree of habitat degradation was higher in the central area and lower in the surrounding area. The change of the degree of habitat degradation showed an upward trend in time, and the areas where the degree of habitat degradation changes were more concentrated in space, such as the urban agglomeration along the river, urban and rural areas and other population agglomerations. [Conclusion] The habitat evolution in the middle and lower reaches of the Yangtze River is in a process of degradation. The process of urbanization makes a large number of woodland, grassland and cultivated land in land use turn to construction land, which leads to the continuous decline of habitat quality, especially the problem of the urban agglomeration. along the Yangtze River. We should develop construction land more reasonably and draw the ecological protection red line, gradually restore and improve the habitat quality of the middle and lower reaches of the Yangtze River, and make a positive contribution to the process of the Yangtze River protection. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to investigate the evolution of ecosystem service value (ESV) and its influencing factors urbanization in the Karst city cluster and to provide a scientific basis for regional eco-environmental protection ecological function zoning, and ecological compensation decision- making. [Methods] Based on the land use data of urban agglomeration of central Guizhou Province from 2000 to 2020, 16 drivers were selected from natural and socio-economic perspectives, and a Markov-FLUS model was constructed to simulate the land use pattern in 2030 under the scenarios of natural development and ecological constraints. Then, the modified ESV coefficients were used to assess the spatial and temporal evolution of ESV and analyze the factors influencing the spatial differentiation of ESV using Geo detector. [Results] (1) The artificial surface seriously encroached on cropland (53%), forest land (12%), and grassland (10%) from 2000 to 2020. Under the ecological constraint scenario, significant nature reserves were effectively protected, and the artificial surface increased by 55 500 hectares, with a slower growth rate. (2) The ESV as a whole showed a trend of rising and then falling, with regulating services (71.08%)> supporting services (23.59%) cultural services (4.51%) supplying services (0.82%). The value of ESV in 2030 under the natural development scenario was 59.211 billion yuan, and that was 58.906 billion yuan under the ecological constraint scenario. (3) The explanatory power of ESV spatial differentiation factors followed the order: area of districts and counties (0.79)>value-added of agriculture, forestry, animal husbandry and fishery (0,51)> value-added of primary industry (0.50)>GDP (0.41)>GDP per capita (0.30)>area of built- up area (0.09)>resident population (0.04). The area of districts and counties, value-added of agriculture, forestry, animal husbandry and fishery, and value-added of primary industry were significantly and positively correlated with ESV, and GDP was significantly and positively correlated with ESV. The area of districts and counties, value-added of agriculture, forestry, animal husbandry and fishery, and value-added of primary industry were significantly positively correlated with ESV, and GDP was significantly negatively correlated with ESV. [Conclusion Regional ecosystem services are mainly regulating services, and water and woodland ecosystems have a more significant impact on the overall ESV, which is the center of gravity of regional environmental protection and ecological construction. [ABSTRACT FROM AUTHOR]

In post-conflict Colombia, the government has prioritized resettlement of displaced people through development of strong rural livelihoods and the sustainable use of natural capital. In this paper, we considered government proposals for expanding payment for ecosystem services (PES) and sustainable silvopastoral systems, and private-sector investment in habitat banking. We coupled the Integrated Economic-Environmental Model (IEEM) with spatially explicit land use and land cover change and ecosystem services models to assess the potential impacts of these programs through the lens of wealth and sustainable economic development. This innovative workflow integrates dynamic endogenous feedbacks between natural capital, ecosystem services and the economic system, and can be applied to other country contexts. Results show that PES and habitat banking programs are strong investment propositions (Net Present Value of US$4.4 and $4.9 billion, respectively), but only when moving beyond conventional economic analysis to include non-market ecosystem services. Where a portfolio investment approach is taken and PES is implemented with sustainable silvopastoral systems, investment returns would reach US$7.1 billion. This paper provides a detailed evaluation of the benefits of investing in rural livelihoods and enhancing Colombia's natural capital base, with empirical evidence to inform the spatial targeting of policies to maximize economic, environmental and social outcomes. [ABSTRACT FROM AUTHOR]

Mountain springs are the only water source for most of the communities in the Kashmir Himalayas. However, over the past two decades, the discharge of these springs has decreased, and some springs have dried up. The current study mapped springs from the Sindh basin of the Kashmir Himalaya via a GPS-based Field survey. The dynamics of spring discharge were evaluated vis-à-vis climatic variability, land use changes, snow cover area, and any major developmental projects in the catchment. The observed temperature and precipitation data were subjected to trend analysis using the Mann Kendall's tau test and Sen's slope estimator. MODIS data were used to understand the dynamics of the Snow Cover Area (SCA) from 2010 to 2021. Landsat satellite imagery was processed to quantify the changes in Land use/cover (LULC). The study found that 13% of the springs below 1600 masl, 22% from 1600 to 2500 masl, and 28.9% above 2500 masl have witnessed a high decrease in discharge. The seasonality of the spring discharge implies snowmelt is the predominant source. The time series analysis shows a weak decreasing trend in the precipitation during the growing season (Spring and Summer). However, both minimum and maximum temperatures show a statistically significant upward trend and result in the early melting of the snow, also confirmed by the analysis of SCA. The study reveals that climate change and LULC change are responsible for the drying of the springs. [ABSTRACT FROM AUTHOR]

Determining groundwater quality status and hydro-geochemistry of an aquifer is crucial to ensure cleaner and safer water for human consumption. Groundwater sustainability issues are getting attraction due to global warming and complexities in land utilization. These concerns increased the challenge of gaining an appropriate comprehension of anthropogenic activities and natural processes, as well as how they influence the quality of surface water and groundwater systems. In the present investigation, 48 groundwater samples were collected and analyzed from the Panchkula district of Haryana, located in the Upper Ghaggar River Basin, to explore the sources and driving factors responsible for hydro-geochemistry of the aquifers falling under the natural and anthropogenically intervened areas. Groundwater sampling was carried out in the premonsoon (PRM) as well as postmonsoon (POM) seasons to examine the spatio-seasonal variations in its quality. The results of the study revealed that reverse ion exchange processes are mainly controlling the aquifer geochemistry in areas occupied by natural vegetation, while the nitrate and chloride content of groundwater was the result of anthropogenic activities. The mechanisms governing groundwater quality and the related hydro-geochemical processes were assessed using binary plots of different cations and anions, along with the Gibbs plot and chloro-alkaline indices (CAI). Saturation indices (SI) indicated that groundwater was over-saturated with respect to dolomite, calcite, and aragonite, while 68.75% and 50% of samples indicated under-saturation with respect to anhydride and gypsum, respectively. Principal component analysis (PCA) and Pearson's correlation coefficients were also considered to affirm the processes taking place to control the aquifer chemistry. Groundwater in the majority of the area was found suitable for drinking purposes except in the locations where high nitrate concentrations were recorded, thus suggesting the use of water treatment facilities for such areas. [ABSTRACT FROM AUTHOR]

In Egypt, planning practice is physical and rooted in design principles, resulting in plans that seldom consider the impact of land use and land cover changes on the environment. Most used planning models are static. The paper offers urban metabolism and dynamic modeling as an alternative mode for decision making. It models population growth and expanded economic activities that characterize rapid urbanization and induce changes in land use affecting various urban economic sectors using the Greater Cairo Region (GCR) as a case study. Urban transportation contributes to climate change. The authors used secondary data and satellite images to detect land use and cover changes since 2005. After building a stock-flow diagram to describe the system's structure, they used dynamic modeling and GIS to assess the impact of transportation on air quality. Results indicate that the population of GCR will range from 33.348 to 40.334 million in 2050. The emissions from transportation will be around 52,521.2 Gg, which is beyond the ability of the region's ecosystems to store carbon. These findings shed doubt about the ability of GCR to reach carbon neutrality and, therefore, call for strict measures to control emitting GHGs and change in planning practices and education. [ABSTRACT FROM AUTHOR]

Rising population and urban expansion have ushered drastic transformations in land use patterns, which can considerably affect soil components and processes. Peri-urban regions at the rural-urban interface are of specific concern because of their dynamic and complex land use pattern. Here, we investigated the spatial variability in soil physicochemical parameters of the surface soil (0–30 cm) in peri-urban landscape of Ghaziabad district, located in the upper Gangetic plain of Uttar Pradesh, India. A total of 45 sites belonging to five different land use classes namely agriculture, park, residential, industrial and bare land were sampled from December 2019 to January 2020. Descriptive analysis of data showed wide variability in the soil properties, with chemical properties being more variable than physical properties. We observed significant differences in soil properties across land use types and their heterogeneous distribution across the three sites. Industrial land use with low vegetation cover was distinctly differentiated from other anthropogenic land use and land cover by high bulk density. Residential land use with high nutrient input from domestic waste and physical disturbance from construction activities was separated from other overlapping land use types by high water-holding capacity and calcium (Ca) concentration. Overall, the results of the study suggest that multifaceted anthropogenic disturbances including modification of parent material, extensive fertilization and irrigation, transportation and waste dumping entail significant changes in soil characteristics and may have serious implications on soil structure and function. Such regional and local studies would help in developing scientifically informed practical measures to improve and maintain the soil quality. Hence, further detailed research exploring the impact of anthropogenic land uses on soil characteristics is needed for management and preservation of the soil mantle. [ABSTRACT FROM AUTHOR]

The increasing trend of transforming fertile land for non-agricultural uses, particularly at the rural–urban interface and city outskirts, has seriously threatened food security in developing countries. However, in an agrarian nation like, Nepal where productive land is minimal due to its challenging geographical terrain, the agricultural land transformation trend and its motivating factors have not been extensively studied. This study emphasizes the shifting land use patterns and factors shaping farmers’ choices for conversion of farmland into non-farm uses in Dhading, Nepal. Land use land cover data analysis revealed that productive agricultural land decreased by 60.28% while non-farm use of land increased by 93.14% in Dhunibeshi Municipality, Dhading between 2013 and 2022. Further analysis using farm-level cross-sectional data shows that 36% of the households are eager to switch from farming to non-farm use. The results from econometric models indicate that socio-economic factors (gender, education, economically active family members, land proportion), vegetable farm attributes (farm income, crop diversification), farm proximity to urban areas, and non-farm firms, and land conversion proposal collectively influence farmers’ decisions regarding agricultural land use change. Promoting widespread adoption of low-cost production technology and making the agriculture sector lucrative could contribute towards sustainable agricultural land management in the future. [ABSTRACT FROM AUTHOR]

Semi-natural grasslands (SNGLs) in Estonia are threatened by abandonment. This threat is leading to concerns about the degradation of biodiversity within grassland communities. Despite the high relevance of economic incentives in this context, how such incentives influence land managers' decision-making regarding the agricultural use of SNGLs has not been investigated. To obtain its socio-ecological implications for policy-making, we developed regionally specific agricultural scenarios (compensation payments, livestock capacity, hey export, and bioenergy production) and an interdisciplinary modelling approach that made it possible to simulate agricultural land use changes through land managers' responses to varied economic conditions. Through this approach, we found that some economic factors hampered the use of SNGLs: the moderate profitability of beef production, labour shortages, and the relatively high profitability of mulching. We observed a positive relationship between SNGLs and habitat suitability for breeding and feeding birds. However, due to the high maintenance costs of SNGLs, the modelling results indicated that increasing the use of SNGLs through public budgets caused crowding-out effects, i.e., the deteriorating market integration of regional agriculture. This study emphasises the need for policy measures aimed at cost-effective, labour-efficient management practices for SNGLs. [ABSTRACT FROM AUTHOR]

It is vital to provide useful hydrological forecasts for urban and agricultural water management, hydropower generation, flood protection and management, drought mitigation and alleviation, and river basin planning and management, among other things. This paper introduces a simple and flexible hydrological time series forecasting framework. Predicting water levels is crucial, given the need for sustainable environmental management. The prognosis should be reasonable to persuade individuals to take proper precautions. While many methods have been developed to predict water levels, here the effectiveness of two approaches to predicting river water levels was assessed. For this purpose, nine years of data were used, which were divided into input data (2014–2021) and validation data (2022), on water levels in the Morava e Binçës river for the Vitia station, in the form of monthly time series records, to identify the best model among those used and to identify the information necessary for water resource management and hazard control. Models Autoregressive Integrated Moving Average(ARIMA) and Error Trend and Seasonality, or Exponential Smoothing (ETS), were examined using the R package to determine the most accurate. The results indicate the applicability of both models, as evidenced by the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The predictive analysis based on historical water levels allowed the identification of distinct periods characterized by high and low water levels between 2022 and 2024, which is important for the area in question due to the numerous flood events occurring here. [ABSTRACT FROM AUTHOR]

The direction and magnitude of soil organic carbon stock (SOCS) change following land use and land cover change (LULCC) are highly uncertain, largely due to the lack of relevant global soil data. Great efforts have been made to build SOCS database at regional, national and even sub-continental scales following LULCC; however, a comprehensive and open-access global database has not yet been developed, hindering a deep understanding of LULCC impact on SOCS dynamics. In this study, we introduce a new global SOCS database for LULCC, compiled from 639 articles documented in the Web of Science through the end of 2023. Targeting five major land uses (cropland, grasslands, forest, plantation, and savanna), this database – named the Global Soil Organic Carbon Stock dataset after Land Use and Land Cover Change (GSOCS-LULCC) – include 1,206 sites with 5,982 records at various sampling depths. The database will enable users to assess the global impact of LULCC on SOCS dynamics and identify the factors that control SOCS changes for specific types of LULCC. The GSOCS-LULCC database is freely available from the Zenodo platform at https://doi.org/10.5281/zenodo.11183819 (Chen et al., 2024). [ABSTRACT FROM AUTHOR]

Microplastics (MPs) are considered pollutants of emerging concern. In rivers, MPs (=5 mm) are transported by currents and deposited in lakes, reservoirs, estuaries, and oceans. In Mexico, MPs in freshwater ecosystems have been scarcely studied. This work aimed to determine the presence of MPs in rivers of the Sierra Gorda Biosphere Reserve (SGBR). Samples of surface water and sediment collected from the Escanela, Jalpan, Ayutla, and Santa María rivers were processed. MPs in water were extracted by direct filtration using nitrocellulose filters with a 1.2 µm pore size; MPs in sediments were extracted by density suspension using a ZnCl2 solution (p ≈ 1.5 g/cm3). The surface of MPs was examined using SEM-EDX, and spectra of trace elements deposited on the MPs were obtained; additionally, MP polymers were characterized with FTIR. Fibers were the most abundant MP forms in both matrices. Up to 110.87 items L-1 were detected in water and 175 items kg-1 (dry weight) in sediments. Surface wear of MPs was observed, and trace elements were detected, including Al, Fe, Cr, Si, and Zn, among others. The polymers identified in MP samples were polyethylene terephthalate, polyester, polypropylene, high-density polyethylene, polyamide, and polystyrene. The test results revealed the presence of MPs with trace metals on their surface in the freshwater ecosystems of the SGBR, which may be related to mining operations in the study area, changes in land use, wastewater discharges, atmospheric transport, and dry and wet deposition. These findings demonstrated the ubiquity of these pollutants and their presence even in areas intended for conservation. [ABSTRACT FROM AUTHOR]

Previous studies have shown that climate change and human activities play an important role in the vegetation dynamics in the Qinling-Daba Mountains of central China. However, which environmental factors including climate, topography, soil and human activities play an important role in the vegetation dynamics and its spatial pattern in the Qinling-Daba Mountains remains to be further clarified. Based on the normalized difference vegetation index (NDVI) data of the growing season from 1986 to 2019 synthesized by Landsat series satellite data on Google Earth Engine, this study aimed to further investigate the spatial pattern of NDVI and its dynamics, and clarify its environmental controlling factors in the Qinling-Daba Mountains using the methods of spatial analysis and Geodetector. The results showed that: (1) the spatial pattern of NDVI in the study area had a U-shaped NDVI distribution in latitude, anti-Ushaped patterns in longitude and with increasing altitude. (2) 2005 was the year of NDVI breakthrough increase, and the vegetation dynamics was divided into two periods according to the result of MK mutation test: the slow increasing period with an increasing rate of 0.25%/a from 1986 to 2004 (R2 0.74), and the rapid increasing period with an increasing rate of 0.30%/a from 2005 to 2019 (R2 0.92). (3) Topography regulating local hydrothermal conditions and soil enriching nutritions played more important influence on NDVI spatial pattern than climate factors (temperature and precipitation) at the regional scale. The effect of land use on NDVI change was stronger than that of climate warming (temperature), and the climate warming in recent decades played a more important role than precipitation on the NDVI dynamics. Research on vegetation patterns, changes and their environmental influencing factors will help the government and other related agencies to formulate plans or policies for infrastructure development and land management, ecological restoration. [ABSTRACT FROM AUTHOR]

Land use and land cover change (LULCC) have profoundly altered land surface properties and ecosystem functions, including carbon and water production. While mapping these changes from local to global scales has become more achievable due to advancements in earth observations and remote sensing, linking land cover changes to ecosystem functions remains challenging, especially at regional scale. Our study attempts to fill this gap by employing a computationally efficient method and two types of widely used high-resolution satellite images. We first investigated the contribution of landscape composition to ecosystem function by examining how land cover and proportion affected gross primary production (GPP) and evapotranspiration (ET) at six macro-landscapes in Mongolia and Kazakhstan. We hypothesized that both ecosystem and landscape GPP and ET are disproportionate to their composition and, therefore, changes in land cover will have asymmetrical influences on landscape functions. We leveraged a computational-friendly linear downscaling approach to align the coarse spatial resolution of MODIS (500 m) with a fine-grain and localized land cover map developed from Landsat (30 m) for six provinces in countries where intensive LULCC occurred in recent decades. By establishing two metrics—function to composition ratio (F/C) and function to changes in composition change (ΔF/ΔC)—we tested our hypothesis and evaluated the impact of land cover change on ecosystem functions within and among the landscapes. Our results show three major themes. (1) The five land cover types have signature downscaled ET and GPP that appears to vary between the two countries as well as within each country. (2) F/C of ET and GPP of forests is statistically greater than 1 (i.e., over-contributing), whereas F/C of grasslands and croplands is close to or slightly less than 1 (i.e., under-contribution). F/C of barrens is clearly lower than 1 but greater than zero. Specifically, a unit of forest generates 1.085 unit of ET and 1.123 unit of GPP, a unit of grassland generates 0.993 unit of ET and GPP, and a unit of cropland produces 0.987 unit of ET and 0.983 unit of GPP. The divergent F/C values among the land cover classes support the hypothesis that landscape function is disproportionate to its composition. (3) ΔET/ΔC and ΔGPP/ΔC of forests and croplands showed negative values, while grasslands and barrens showed positive values, indicating that converting a unit of forest to other land cover leads to a decrease in ET and GPP, while converting units of grassland or barren to other land cover classes will result in increased ET and GPP. This linear downscaling approach for calculating F/C and ΔF/ΔC is labor-saving and cost-effective for rapid assessment on the impact of land use land cover change on ecosystem functions. [ABSTRACT FROM AUTHOR]

Introduction: The selection of an optimal scale or granularity in landscape analysis is pivotal for uncovering inherent patterns and changes driven by processes. Variations in spatial resolution can significantly alter the proportions and distributions of various landscape types, thereby impacting the assessment of landscape patterns. Despite its importance, the scale factor is frequently neglected in studies focusing on long-term landscape dynamics. Methods: Bridging this gap, we utilized remote sensing imagery data from 1986 to 2020 for Lushui City, integrating remote sensing (RS) and geographic information system (GIS) technologies to generate land cover maps. Our focus centered on investigating the sensitivity of landscape pattern indices within the 30-1000m scale. Combining the first scale domain with an information loss assessment model, we identified the optimal granularity for the analysis, conducting a detailed spatiotemporal examination of landscape pattern from 1986 to 2020 using the index analysis method. Results and discussion: The results show that: (1) The dominance of forests in Lushui City, yet reveal a significant increase in construction land area over the study period, primarily driven by the conversion of forest and grassland. (2) Among the 10 examined indices, four (PD, ED, TE, and LSI) demonstrated predictable responses to changes in granularity, while three (PAFEAC, COHESION, AI) exhibited unpredictable stepwise reactions. Three indices (LPI, SHDI, PLAND) displayed minimal regularity to granularity changes. (3) The optimal long-term landscape analysis granularity for Lushui was identified as 100 m. (4) Before 1996, the city's landscape exhibited characteristics of aggregation, good connectivity, and minimal anthropogenic disturbance. However, post-1996, the landscape experienced disruptions, leading to an overall increase in fragmentation. The expansion of cultivated land and construction land due to urbanization has intensified landscape fragmentation. However, policies such as converting cropland to forest and planned ecological civilization initiatives have restored forest coverage and improved landscape cohesion and connectivity in Lushui City. This research offers vital insights for ecological planning and resource management in alpine valley watershed cities, deepening our grasp of landscape pattern evolution. [ABSTRACT FROM AUTHOR]

Establishing a decision-making scheme for multiple land use types in a shrinking society is an urgent and persistent task. In particular, residents and governments face the complexity of cross-sectoral visions over concerned landscapes. This study examined the preference of residents for future visions and the effects of group deliberation in a Japanese rural community to enhance the current understanding of decision and learning processes on cross-sectoral land use types (i.e., agricultural land, forest land, and boundary areas) across ages and groups. This study posed the following questions: (i) what types of interactions do residents find among options on cross-sectoral land uses? and (ii) how do group deliberation influence the individual preferences of residents for land use? In the survey, the residents disclosed their preferences for the prepared visions over three land use types. The survey also enabled the comparison of choices before and after group deliberation. Regarding question (i), the residents' choice prior to the deliberation demonstrated thematic coherence through land use categories. Smart technology and potential productivity improvement were selected across agriculture and forests. However, regarding question (ii), thematic coherence decreased after the group deliberation. The residents could communicate disagreements during group deliberation and consider the issues relatively independently over land use types, which separately views agriculture lands and forests. The choice after group discussions became increasingly embedded and influenced by residential areas and land ownership of residents. These findings provide unique insights into the group discussion on how individual decisions are affected. In summary, the preferences of cross-sectoral land use types did not converge but tended to diverge. [ABSTRACT FROM AUTHOR]

Rapid urbanization induces significant changes in land use, exerting a profound impact on regional habitat quality. Understanding the interconnectedness of urbanization and habitat quality is crucial for safeguarding the regional ecological environment and promoting sustainable urban development. Cities along the Yangtze River, as the core region of the Yangtze River Economic Belt in China, serve as a typical and critically important area to investigate the dynamic response of habitat quality to rapid urbanization. This study employs the InVEST model and entropy method to assess the spatiotemporal dynamics of habitat quality and urbanization in Yangtze River cities. Using the coupling coordination degree model, it analyzes the interplay between urbanization and habitat quality, elucidating dynamic response patterns and emphasizing the need for pertinent policy measures. Our findings reveal that from 1990 to 2019, urbanization levels in the study area surged by over six times, while habitat quality consistently declined, reflecting a 4.5% decrease. Notably, spatial variances were observed along the upstream, midstream, and downstream segments of the river. Although an inverse relationship between urbanization and habitat quality predominates, three cities demonstrated a positive correlation. The study also indicates a stable increase in the coupling coordination degree between urbanization and habitat quality, evolving from a phase of urbanization lag to one of synchronization followed by habitat quality lag. Among the cities, Chongqing emerges as an exemplary model for the coordinated development of urbanization and habitat quality. These insights provide a theoretical foundation and policy guidance for enhancing sustainable urban and ecological strategies in the region. [ABSTRACT FROM AUTHOR]

The growing awareness of environmental issues, climate policies, and rapidly developing technologies is contributing to the increasing number of battery electric vehicles (BEVs) around the world. A key requirement for their widespread implementation is providing a charging infrastructure that allows users to operate these vehicles comfortably. Lack of access to charging stations can be a major barrier to the development of electromobility in a given area. Therefore, each additional charging infrastructure can support a change in the structure of the vehicle fleet. One of the key challenges facing this transformation is the selection of suitable locations for charging stations. It is necessary to ensure that they are uniformly distributed so that range anxiety for EV users is reduced and equal access to charging infrastructure is provided to all residents. One of the most important stakeholders in this market is local authorities. Therefore, the objective of this research was to develop a method of determining optimal locations for electric vehicle charging stations (EVCSs) from the perspective of local authorities that also takes into account equal access to the charging infrastructure for all residents, which seems to be a unique approach to this problem. We used commonly available spatial data as input to enable the method to be applied on a larger scale and over an urban area. We carried out our research using a case study: the city of Gliwice in Poland. The city area was divided into hexagonal basic fields, for which potentials for locations of new charging stations were calculated. The analysis was carried out using the geographic information system (GIS) QGIS (ver. 3.34). [ABSTRACT FROM AUTHOR]

Land use is both a major cause of the biodiversity crises and a potential solution to it. Decisions about land use are made in complex social–ecological systems, yet conservation research, policy, and practice often neglect the diverse and dynamic nature of land use. A deeper integration of land system science and conservation science provides major opportunities in this context, through a transfer of concepts, data, and methodologies. Specifically, a closer exchange between land‐use data developers and users will enable common terminology and better data use, allowing to move beyond coarse land‐cover representations of land use. Similarly, archetyping and regionalization approaches can help to embrace, rather than oversimplify, the diversity of land‐use actors and practices. Finally, systematically linking land‐use actors to portfolios of pressures on biodiversity, beyond their direct impact on habitat, can better represent and map co‐occurring and interacting threats. Together, this will enable conservation policymakers and planners to recognize the often‐complex and wicked nature of conservation challenges related to land, allowing for more context‐specific conservation policymaking and planning, and more targeted conservation interventions. [ABSTRACT FROM AUTHOR]

Net Primary Productivity (NPP) is a crucial indicator of ecological environment quality. To better understand the carbon absorption and carbon cycling capabilities of Henan Province, this study investigates the trends and driving factors of NPP across different climatic zones and land use types. The Theil–Sen Median trend analysis method and the Mann–Kendall trend test are employed to monitor NPP changes from 2001 to 2020. The average annual NPP in Henan Province during this period was 414.61 gC·m−2·year−1, showing a significant increasing trend with a growth rate of 3.73 gC·m−2·year−1. Spatially, both the annual average NPP and its increase rate were higher in the western part of Henan compared to the eastern part, and NPP variability was more stable in the southern region than in the northern region. By classifying climatic zones and using the Geodetector method to assess NPP sensitivity to natural factors, the results show that climate and vegetation factors jointly influence NPP variations, with annual precipitation being the primary natural factor affecting NPP trends in Henan Province from 2001 to 2020. By analyzing the NPP gain and loss matrix, the impact of land use changes on NPP was evaluated. Forests had the highest average annual NPP at 483.52 gC·m−2·year−1, and the conversion of arable land to urban areas was identified as the primary land change type leading to NPP reductions. In the subtropical zone of Henan, forests, croplands, and grasslands exhibited higher NPP values and increase rates compared to those in the warm belt. This study provides new insights into the spatial variation of NPP caused by changes in climatic zones and land use types. [ABSTRACT FROM AUTHOR]

This study evaluated the lead (Pb) immobilization efficiency of biochar in contaminated agricultural soil. The biochar was produced from a range of major biomass residues and pyrolyzed under well-controlled conditions. Ten different types of standard biochar samples were derived from five different feedstocks (i.e., softwood, miscanthus straw, rice husk, oilseed rape straw, wheat straw) and pyrolyzed at 550 ℃ and 700 ℃. Pb-contaminated soil near an abandoned mine was incubated with 2.5% (w w− 1) of biochar. Incubation was conducted for various durations at room temperature under both short-term (21 days) and long-term (214 days) conditions. This variation explicitly accounted for the simulated microplastic contamination during the long-term incubation period. A novel framework has been developed to predict the long-term immobilization effect of various biochar types using a machine-learning approach, following the successful identification of optimal biochar implementations. This prediction method utilizes a small on-field dataset by employing a data augmentation approach, showcasing an innovative approach to forecasting the effects of different biochar types over time. After the incubation period, soil samples were analyzed for their chemical properties. As a result, oil seed rape biochar was the highest in pH, EC, exchangeable Ca2+, Mg2+, and K+, total nitrogen content, soil organic matter content, and available phosphate. In return, OSR 700 treated soils showed the highest content of exchangeable cations and the lowest content of available Pb after the incubation period. The most efficient biochar for immobilizing lead (Pb) in soil appears to be OSR 700, based on the available evidence. [ABSTRACT FROM AUTHOR]

Over the past two decades, Addis Ababa has witnessed a relentless transformation in its land use and land cover. Primarily driven by the conversion of agricultural land through extensive expropriation in the city's expansion areas. The study explores the dynamic land use land cover changes and associated land expropriations from peri-urban farmers in the rapidly growing Addis Ababa, Ethiopia. The study utilized a time series of global land cover and land-use change datasets (GLAD) covering the years 2000-2020. Moreover, empirical data is gathered through a household survey conducted among 349 systematically selected expropriated farmers across four sub-cities of Addis Ababa. The findings underscore a profound shift in the city's land use and land cover over the past two decades. The built-up area emerges as the predominant land cover, witnessing a substantial increase of 25.28% (13,150.30 ha) over the past two decades. Concurrently, agricultural land and vegetation cover decreased by 15.92% and 9.35%, respectively, indicating a significant outward expansion of the city. This expansive growth, driven by the city's rapid development, has resulted in extensive land expropriations primarily affecting peri-urban farmers. The expropriations were mainly for housing, investment, industrial parks, and infrastructure development. Thus, we urge the city administration to carefully manage the horizontal expansion of builtup areas at the expense of the agricultural land and vegetation cover. Finally, we recommend holistic and sustainable development strategies, developed collaboratively with local communities and planners, to safeguard the longterm wellbeing of city residents. [ABSTRACT FROM AUTHOR]

As an urbanization effort propelled by administrative measures, city-county merger has been particularly prevalent in the administrative district adjustments of prefecture-level cities in China. However, there has been scant research focusing on the policy's impact on the efficiency of green utilization of urban land. We selected panel data from Chinese prefecture-level cities from 2003 to 2020, employing the slack-based measure (SBM) model that accounts for undesirable outputs, in conjunction with the Malmquist-Luenberger (ML) productivity index, to measure the efficiency of green land use in cities. Building on this, we utilized the staggered difference-in-differences (DID) model to investigate the impact of policies expanding cities through land leasing on the green utilization efficiency of urban land. Our findings indicate that the city-county merger has generally led to a decline in the efficiency of green utilization of urban land. Further mechanism analysis suggests that local governments' excessive focus on land leasing for economic development, leading to a low-quality development model, is a significant factor contributing to the decline in green utilization efficiency of urban land. Specifically, the city-county merger policy indirectly reduces land green utilization efficiency by increasing industrial land leasing revenue, the number of industrial polluting enterprises, lowering the rationalization level of urban industrial structure, and raising the overachievement of urban economic growth targets. Further research reveals that the policy has heterogeneous impacts on land green utilization efficiency across different regions, city sizes, administrative levels, economic development levels, and urban planning types. The policy has a more significant inhibitory effect on land green utilization efficiency in non-eastern regions, smaller cities, peripheral cities, underdeveloped cities, and resource-based cities. Our study confirms that as a significant urbanization reform initiative, the effectiveness of the city-county merger still relies on the traditional extensive growth model based on land expansion, which is not conducive to enhancing the efficiency of green land use in cities. [ABSTRACT FROM AUTHOR]

In Burkina Faso, as in other Sahelian countries, natural pastures are a key element in managing livestock productivity, as they are the main source of feed. This is why, after the droughts of 1970, the government of Burkina Faso created pastoral zones to boost livestock productivity. However, the results of this project remain unsatisfactory. This study therefore aims to assess pastoral resources by analysing the dynamics of pastoral landscapes in the Niassa pastoral zone. To this end, remote sensing and perception surveys of pastoralists were used. From 2000 to 2020, the dynamics of land use shifted away from grazing areas. Indeed, the rate of occupation of cropland rose from 15.35% in 2000 to 39.33% in 2020 and that of bare lands from 2.46% to 7.62% with a decrease of 46.95% in pastureland. This has a negative impact on pasture biomass production and herd management. Thus, 91% of the pastoralists surveyed perceive this dynamic through the low availability in quantity and quality of fodder resources. They believe that herbaceous species of high value to livestock are disappearing. They are Andropogon gayanus, Andropogon ascinodis and Vetiveria nigritana according to respectively to 83%, 80%, and 78% of respondents. These species have been replaced by less valuable or with low biomass production species such as Senna obtusifolia, Hyptis suaveolens, Loudetia togoensis, Microchloa indica and Zornia glochidiata according respectively to 100%, 90%, 90%, 95%, and 65% of respondents. According to respondents, the endangered woody species are Pterocarpus erinaceus (88.4%), Afzelia africana (64%), Bombax costatum (58%), Vitex doniana (55%) and Khaya senegalensis (55%). The reduction in pastureland, forage species and forage availability are indicative of the degradation of the pastoral zone. This is leading to a drop in livestock productivity and, consequently, the impoverishment of pastoralists and agropastoralists. [ABSTRACT FROM AUTHOR]

Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling. Microbial carbon use efficiency (CUE) is crucial for carbon storage, but its variability is difficult to capture due to inconsistent measurements and complex interactions. This perspective proposes integrating diverse data and models to improve CUE in carbon cycle models [ABSTRACT FROM AUTHOR]

Soil nutrient levels play a crucial role in determining crop yield. A comprehensive understanding of the spatial distribution patterns and evaluation grades of soil nutrients is of significant practical importance for informed fertilization practices, enhancing crop production, and optimizing agricultural land utilization. This study focuses on the urban area of Kashi Prefecture in Xinjiang as a case study. Utilizing soil sample data, GIS spatial interpolation analysis was conducted, incorporating plot boundary information to propose a comprehensive evaluation method for assessing soil nutrient levels at the plot level. Experimental findings revealed the following: (1) The average values of soil organic matter (SOM), total nitrogen (AN), total potassium (AK), and total phosphorus (AP) in the study area were determined to be 13.3 g/kg, 0.74 g/kg, 0.33 g/kg, and 0.03 g/kg, respectively. Among these, AN and SOM were classified as the fourth grade, indicating relatively deficient levels, while AK and AP were classified as the first and second grade, indicating relatively abundant levels. (2) The comprehensive evaluation of soil nutrient grades in the study area primarily fell within the third, fourth, and second grades, representing areas of 29.08 km2, 25 km2, and 4.05 km2, accounting for 50.03%, 43%, and 6.97% of the total area, respectively. (3) The evaluation results of soil nutrient levels at the plot level emphasized the boundary characteristics and provided a more refined assessment grade. This evaluation method is better suited to meet the practical production requirements of farmers and is considered feasible. The outcomes of this study can serve as a reference for precision agriculture management. [ABSTRACT FROM AUTHOR]

Introduction: Creating an ecological space network is essential for safeguarding the core structure of ecological space. Methods: Morphological spatial pattern analysis was used to locate ecological sources in the Kuye River Basin. Using the least cumulative resistance model and gravity model, the resistance surface, ecological corridor, and ecological space management network are determined. Results and discussion: The study revealed that in 2022, the predominant land use types in the Kuye River Basin were wood land and grassland, cultivated land, and construction land. MSPA model software identifies a substantial portion of the landscape pattern as consisting of core and marginal areas, which encompass 30324.05 hm² and 15088.24 hm². High ecological resistance surface factors dominate the socioeconomically vibrant zone and northern regions. Resistance values ranging from 0.02 to 0.87, and high and law resistance zones alternate. The minimal cumulative resistance approach found 171 ecological corridors. And gravity model using the interaction matrix of 19 primary ecological sources discovered 8 first-level ecological corridors with the highest interaction force. There are 137 core and 23 subsidiary ecological corridors with significant affects. Overlying the road factors and ecological corridors of national highways, provincial roads, railways, and high-speed roads creates a total of 38 ecological breakpoints, each characterized by specific barrier effects and legal ecological stability. [ABSTRACT FROM AUTHOR]

The stability of soil organic carbon (SOC) is crucial for the global carbon cycle and serves as a key indicator of soil quality and eco-system function. In Karst areas, SOC stability is influenced by unique geological conditions. Studying SOC stability in these regions is significant for understanding regional ecosystem functions and the role of SOC in mitigating global climate change. This review examines the fractions and stability of SOC in Karst areas, analyzing the impacts of key factors such as rocky desertification, land use changes, and vegetation restoration on SOC stability, along with their underlying mechanisms. It also discusses the current challenges and opportunities in SOC stability. This review aims to guide the development of effective ecological rehabilitation and management strategies for degraded ecosystems in Karst areas. [ABSTRACT FROM AUTHOR]

Human activities have profound impacts on land use and the supply–demand balance of ecosystem services (ESs). Various activities, such as urban construction, urban and rural planning, and inter-basin water transfer projects, continuously reshape land use patterns. This is a case study of the Anhui section of the Yangtze-Huaihe Water Diversion Project. Data from 2000, 2010, and 2020 is analyzed. Additionally, the patch-generating land use simulation (PLUS) model is utilized to quantify the specific impacts of the water diversion project construction on the supply and demand of ESs. The results indicate that the comprehensive dynamic attitude of land use during the project construction period significantly increased, rising from 0.16 to 13.79%, and mainly affected forest, water areas, construction land, and unused land. Specifically, the construction of the project led to significant changes in water purification, biodiversity, and, especially, hydrological regulation services. Additionally, the migration of residents significantly impacted the demand for ESs. The study also found a significant correlation between land use changes and the balance of ES supply and demand: the proportion of cultivated land and construction land is positively correlated with the balance, while the proportion of forest, grassland, and water areas is negatively correlated. This study provides empirical data for understanding the environmental and socio-economic impacts of large-scale water diversion projects and offers a scientific basis for local mitigation and control of adverse impacts. Through quantitative analysis and model prediction, this research effectively bridges the gap between theory and practice, providing important references for sustainable regional development. [ABSTRACT FROM AUTHOR]

Reducing the environmental pressures stemming from food production is central to meeting global sustainability targets. Shifting diets represents one lever for improving food system sustainability, and identifying sustainable diet opportunities requires computational models to represent complex systems and allow users to evaluate counterfactual scenarios. Despite an increase in the number of food system sustainability models, there remains a lack of transparency of data inputs and mathematical formulas to facilitate replication by researchers and application by diverse stakeholders. Further, many models lack the ability to model multiple geographic scales. The present study introduces Foodprint 2.0, which fills both gaps. Foodprint 2.0 is an updated biophysical simulation model that estimates the agricultural resource requirements of diet patterns and can be adapted to suit a variety of research purposes. The objectives of this study are to: 1) describe the new features of Foodprint 2.0, and 2) demonstrate model performance by estimating the agricultural resource requirements of food demand in the United States (US) using nationally representative dietary data from the National Health and Nutrition Examination Survey from 2009–2018. New features of the model include embedded functions to integrate individual-level dietary data that allow for variance estimation; new data and calculations to account for the resource requirements of food trade and farmed aquatic food; updated user interface; expanded output data for over 200 foods that include the use of fertilizer nutrients, pesticides, and irrigation water; supplementary files that include input data for all parameters on an annual basis from 1999–2018; sample programming code; and step-by-step instructions for users. This study demonstrates that animal-sourced foods consumed in the US accounted for the greatest share of total land use, fertilizer nutrient use, pesticide use, and irrigation water use, followed by grains, fruits, and vegetables. Greater adherence to the Dietary Guidelines for Americans was associated with lower use of land and fertilizer nutrients, and greater use of pesticides and irrigation water. Foodprint 2.0 is a highly modifiable model that can be a useful resource for informing sustainable diet policy discussions. [ABSTRACT FROM AUTHOR]

A reasonable land use development around subway stations can balance the utilization rates of the subway system during peak and off-peak hours, thereby enhancing its service levels and operational efficiency. Analyzing the temporal distribution patterns of passenger flow and their influencing factors is crucial for determining the optimum ratio of each land use type surrounding metro stations. Thus, this paper employs principal component analysis (PCA) at first to investigate the temporal distribution of metro ridership, and identify their main patterns and factor loadings. Then, using geographically weighted regression, the study examines the spatial dependencies between the main component proportions and influencing factors, focusing on Xi'an subway stations. The results indicate that the temporal distribution of passenger flow can be decomposed into three principal components: the first representing commuting characteristics, and the second and third representing regulating functions. The overall distribution is a composite of these components in varying proportions. Residential and educational land uses primarily drive morning and evening peak flows, with residential land use in the city center and peripheral areas having a more pronounced effect compared to transitional areas. Conversely, commercial & office, healthcare, and recreational & park land mitigate peak flows and increase off-peak flows. External hub enhances passenger flow throughout the day, while industrial land use has negligible impact. [ABSTRACT FROM AUTHOR]

In this paper, the original RSEI model (including greenness index, humidity index, heat index and dryness index) and their contribution rate (%) are used to evaluate the change of ecological environment. To study how natural and anthropogenic changes in ecological environment affect ecosystem function and how these factors interact, CASA model was used to estimate the correlation between the net primary productivity of vegetation (NPP), population density and land use. This could reveal the influence factors of ecological environment change in the Wanjiang River Basin from 2000 to 2022. The results show that the combing RSEI and CASA models can effectively show the spatial-temporal variation and spatial distribution of NPP of vegetation in Wanjiang Basin. During this period, RSEI of the basin showed an overall upward trend, and the RSEI increased by about 0.1/ 10 a. The vegetation productivity in most areas was gradually improved, the ecological environment was restored, and the ecological environment quality was gradually improved. The average annual NPP simulated by CASA was 266.81 g C-m-2-a-1 The variation trend of NPP in vegetation showed a slight decrease, but the overall NPP level was basically unchanged. There is a significant correlation between NPP and population density, a negative correlation between NPP and population density areas such as city centers, and a positive correlation between NPP and population density in areas with frequent agricultural activities. From 2010 to 2020, there is a significant positive correlation between population density and land use. [ABSTRACT FROM AUTHOR]