This study investigates the impact of landscape patterns on ecosystem services in the Ruoergai Plateau from 1990 to 2020. Ecosystem services play a crucial role in maintaining the balance of natural ecosystems and facilitating socio-economic development. Using the InVEST model, it quantifies and assesses carbon storage, soil conservation, water yield, and habitat quality. Correlation analysis is employed to explore the interrelationships and constraints among different ecosystem services, while stepwise regression analysis and bivariate spatial autocorrelation are utilized to investigate the impact mechanisms of landscape patterns on ecosystem services. Results indicate that the Ruoergai Plateau has experienced changes and transitions in land use, with grasslands being the primary type showing a decreasing trend. Landscape patterns have significantly altered, with a mitigation of fragmentation observed. Overall, ecosystem services show a declining trend initially followed by an increase. Carbon stock showed a decreasing trend from 1990 to 2010, with a significant increase from 2010 to 2020 and an increase of 0.41 × 108 t. The average carbon density and stock in the study area in 2020 reached 78.48 t.hm- 2 and 3.64 × 108 t, which were mainly concentrated in the wetland and forested land, distributed in the eastern and southwestern parts of the study area. There exist varied trade-offs and coordination among ecosystem services across different regions and temporal scales, while demonstrating a certain correlation with landscape indices. These findings enhance our understanding of how landscape pattern dynamics shape ecosystem service functions, providing valuable insights for regional ecological management and sustainable development.

Tick-borne zoonotic diseases continue to emerge in North America and Europe. Of particular concern are pathogens transmitted by Ixodes ticks, such as Borrelia spp., the causal agents of Lyme disease (Lyme borreliosis). Because Ixodes ticks are adapted to forested habitats with high humidity and depend on wildlife for feeding and movement, research has focused on natural or rural landscapes. Demographic and land-use transitions, however, have created novel ecosystems in urban and periurban areas with high potential for human exposure. We describe post-World War II land processes giving rise to these ecosystems and explore resource-based habitat concepts and top-down community ecology perspectives aimed at predicting tick-borne disease (TBD) risk. We review studies in Europe and North America that demonstrate TBD risk in urban areas and potential drivers for TBD emergence. We identify missed opportunities for data measurements and reporting and propose metrics to quantify landscape connectivity to facilitate future syntheses or meta-analyses.

Regional heterogeneity in groundwater response driven by land-use transitions across Pakistan

Urbanization-driven risk assessment of song-dynasty cultural heritage under land-use transition: A landscape-based spatial model for historic Kaifeng, China

Systematic biodiversity and ecosystem service (ES) conservation is vital for ecological sustainability and human well-being. This study combines MaxEnt, Zonation, InVEST, and MSPA models to identify Conservation Priority Areas (CPAs) in the Wujiang River Basin (WJRB), integrating biodiversity hotspots, ESs, and landscape connectivity. Results reveal CPAs span 1.13 × 104 km2 (primarily downstream), but existing natural reserves (NRs) cover only 24.86% of these critical zones, leaving over 75% unprotected in this region. Current NRs occupy 0.62 × 104 km2, with 5.82% of the basin (mainly upstream) available for targeted expansion. Spatial analysis reveals mismatches, such as some NRs protecting low-value ecological areas, resulting in imbalanced coverage. Expanding NRs across the board is less effective than adjusting protection scope or management strategies in areas of spatial mismatch, based on identified CPAs. This can involve establishing new reserves and appropriately relaxing land-use restrictions to allow compatible activities within them. New conservation planning should prioritize large, interconnected CPA regions to enhance landscape coherence. Simultaneously, integrating ecological compensation mechanisms can align protection goals with local livelihood improvements, fostering community engagement. This approach addresses critical gaps and enhances conservation efficiency by strategically directing resources toward high-value, vulnerable ecosystems. The methodology offers a replicable framework for balancing ecological preservation and human needs in river basin management.

Ecosystem services (ES), as a link between human activities and natural ecosystems, are crucial for maintaining ecological balance and supporting economic development. Ecosystem Services Value (ESV) is an indicator used to quantify ecosystem services. Accurately estimating the dynamics of ESV and its influencing factors is significant for regional sustainable development. This paper constructs an ESV valuation model incorporating construction land based on the modified equivalence factor method. It also examines the dynamic evolution of land use and ESV in the study area, as well as the interactions and influencing factors of ESV, using methods such as land-use transition matrix, ESV trade-off and synergy analysis, and XGBoost-SHAP models. The results show that: (1) during the study period, the changes in the single dynamics of cultivated land and construction land in the middle reaches of the Yellow River were significant, at -2.953% and 1.897%, respectively. The overall land dynamic rate averaged 0.152%, peaking between 2005 and 2010. Land-use type conversion was mainly between cultivated land, forest, and grassland. (2) ESV in the middle reaches of the Yellow River gradually decreased, with a total reduction of 21.951%. Areas with lower and middle ESV values contracted, while the remaining levels expanded, showing a spatial distribution pattern of decreasing from northwest to southeast. (3) The degree and direction of interactions between various ecosystem services in the study area changed over the 24 years, with the extremes of trade-off and synergy increasing. The relationship between water supply services and other services was the most significant. (4) Nighttime light brightness was the primary factor affecting ESV changes in the middle reaches of the Yellow River. Average slope, forest proportion, and annual average temperature had a positive impact on ESV, while nighttime light brightness, cultivated land proportion, population density, and average elevation had a negative impact. Other factors had minimal influence. The findings of this study provide important theoretical support for the formulation of targeted ecological protection measures, promoting the sustainable development of the Yellow River Basin.

Abstract Urban traffic noise is associated with the health and living environment quality of residents. As urbanization and population density continually increase, it is vital to understand and predict the impact of urban design behavior on urban traffic noise. Despite the current progress has been made in modeling traffic noise using limited land use types, understanding the complex relationship between various land uses and traffic noise remains challenging for stakeholders. This study used generative adversarial networks with Hong Kong one-hour peak traffic noise map to predict urban traffic noise. The applicability of the training model was evaluated through accuracy analysis and validation. The validated model was used to generate the predicted noise map in multiple scenario experiments by adjusting controlled variables. This approach explores how land use changes effect the noise level, with scenario experiments highlighting both effective strategies and areas requiring further validation.

Understanding the evolutionary dynamics of land use and habitat quality (HQ) under climate change scenarios is pivotal for formulating science-based biodiversity conservation policies and promoting climate-resilient urban development in arid regions. By integrating the SD–PLUS–InVEST framework with SPEI-driven drought scenarios, this study introduces a novel coupling mechanism that links climate variability, land-use transitions, and HQ evolution in the Northern Slope of the Tianshan Mountains (UANSTM) under SSP–RCPs scenarios. The HQ assessment was validated using the Remote Sensing Ecological Index (RSEI). Simultaneously, the Optimal Multivariate-Stratification Geographical Detector (OMGD) was applied to identify scale-optimized drivers of HQ changes. The results indicated the following: (1) From 2000 to 2020, cultivated and construction land in the UANSTM expanded, while forest and water areas declined, with unused land remaining dominant from 2000 to 2020. (2) HQ decreased from 0.36 to 0.33 (2000–2020), significantly correlating with RSEI (Pearson r = 0.329, Spearman ρ = 0.446, p < 0.001), with climatic, vegetation, and coupled natural-social factors remaining the dominant drivers. (3) From 2020 to 2050, under all climate scenarios, the areas of farmland, grassland, and construction land are expected to grow, while HQ is projected to improve through the conversion of low-quality areas into moderate- and high-quality habitats (greatest under SSP119, least under SSP585). The framework advances predictive insights for arid-region ecological planning, supporting practical applications in habitat management and sustainable land-use planning, while providing a methodological paradigm for dryland habitat resilience assessment.

Abstract Aims This study explores the geochemical consequences of converting long-term flooded rice fields to non-flooded pomegranate orchards in calcareous, organic-rich soils of Southern Italy. Methods By analyzing topsoil (0–20 cm) and subsoil (50 cm) samples, we investigated how land-use change influences the distribution, speciation, and mobility of iron, copper, zinc, manganese, aluminum, phosphorus, and silicon. Sequential extraction, Mössbauer spectroscopy, and elemental analyses were employed to assess shifts in redox-sensitive mineral phases and nutrient pools. Results The transition to aerobic conditions induced substantial alterations in iron fractionation, including the loss of amorphous and acid-soluble phases and increased crystallization into more stable reducible forms. Despite these structural changes, Mössbauer spectroscopy revealed that iron redox states remained largely unaffected, indicating strong valence-state resilience. Copper became more strongly associated with manganese and (amorphous) iron oxides, while its acid-soluble fraction declined significantly, particularly in the subsoil. In contrast, zinc remained largely immobilized within the residual fraction, demonstrating greater geochemical stability. Conclusions Our findings underscore the complex interaction between redox conditions, mineral transformations, and nutrient dynamics during land-use transitions. Understanding these processes is critical for managing soil fertility and minimizing environmental risks in Mediterranean agroecosystems.

Afforestation plays a vital role in reshaping land systems and enhancing carbon sequestration, particularly in ecologically fragile regions. However, the carbon implications and spatial dynamics of large-scale planted-forest (PF) expansion in the Yellow River Basin (YRB) remain insufficiently understood. Focusing on the YRB, this study integrates multi-source land-use, forest type, and carbon datasets to evaluate land-use transitions (2000–2020) and quantify changes in total ecosystem carbon (TEC), aboveground carbon (AGC), and PF-derived AGC (PF-AGC) from 2005 to 2020 under the IPCC-based accounting framework. The results show cumulative land-use conversion of 118,481 km2, with forest land expanded to 11.89% of the basin, mainly due to afforestation efforts in the middle reaches. TEC followed a rise–decline–rebound trajectory, yielding a net gain of 1.96 × 108 t, while AGC increased by 4.37 × 108 t. With the expansion of PF, PF-AGC contributed 1.60 × 108 t (36.61% of AGC gains), primarily sourced from grassland (40.51%), natural forests (35.15%), and cropland (23.56%). PFs were dominated by young stands (≤40 years), spatially clustered in the middle–lower reaches, and exhibited higher carbon sink potential than natural forests. Spatially, AGC and PF distributions underwent staged reconfiguration. Standard deviational ellipse and centroid analyses revealed eastward shifts and axis changes in AGC, and southwestward migration of PFs, indicating PF expansion as a major driver of carbon redistribution. These findings clarify the forest age–land-use–carbon nexus and highlight the spatial impact of afforestation, offering critical insights for region-specific low-carbon strategies and sustainable land governance in the YRB.

This study aims to analyze the social, economic, and technical characteristics of cattle farmers in Salahutu District, Central Maluku Regency. The research was conducted in May–June 2025, involving 30 respondents selected through purposive sampling from three villages: Suli, Tulehu, and Liang. Data were collected through observation, structured interviews using questionnaires, and documentation, and then analyzed descriptively using frequency distribution and percentages. The results showed that most farmers were in productive age with considerable farming experience, although their formal education level was relatively low. Cattle farming was still small-scale, with an average ownership of 8.33 heads per farmer, limited land use, and feed sources mainly from local forages and grazing lands. The main challenges faced by farmers included limited capital, seasonal feed availability, and restricted market access. Nevertheless, the high demand for beef offers significant opportunities for developing cattle farming in the region. This study is expected to serve as a reference for policymaking in improving cattle productivity and farmers’ welfare.

Green transition of urban land use: Spatial spillover effects and boundaries on urban land use efficiency

This study aims to develop a Smart Farming Hydroponic system based on IoT (Internet of Things) technology using the NFT (Nutrient Film Technique) for cultivating Shanghai Pakcoy. Utilizing the Arduino UNO R4 WiFi as the main microcontroller, the research integrates TDS and pH sensors to enable real-time monitoring of AB mix nutrient levels and water acidity. All data collected by the system is processed using the Arduino Cloud IoT Remote platform, allowing for remote monitoring and automated control. The study is conducted in Kampung Buah Tilu, Desa Cisaat Padarincang, focusing on optimizing limited land use in rural areas to introduce modern agricultural technology. The system is designed to enhance cultivation efficiency by maintaining nutrient and pH parameters within optimal ranges for plant growth. Additionally, the scope of the research is limited to technical aspects of nutrient management, excluding temperature and humidity control. The findings indicate that the Smart Farming Hydroponic NFT (Nutrient Film Technique) system successfully improves cultivation efficiency, provides real-time data visualization, and ensures optimal conditions for Shanghai Pakcoy growth. This research not only offers an efficient and eco-friendly agricultural solution but also opens up opportunities for developing similar technologies to empower rural communities. Through this innovation, IoT (Internet of Things) technology can be applied to sustainable farming systems to enhance productivity and improve agricultural product quality.

Mountains, a complex socio-ecological system, are home to 915 million people. The Himalayas, the planet’s youngest mountain range, are critical in shaping the region’s climate, biodiversity, and culture. The Indian Himalayan Region (IHR), spanning 13 Indian states and union territories, holds immense cultural, ecological, and social significance. IHR is geologically active, earthquake-prone, and faces several threats from climate change and human activities. Despite these vulnerabilities, the IHR’s population continues to grow, and many areas are experiencing rapid urbanization. However, there are limited granular (town-level) assessments on the spatial and temporal patterns of urbanization in IHR and its associated vulnerabilities. This case study examines spatial and temporal trends and associated vulnerabilities of urbanization in three towns of the Uttarkashi district of Uttarakhand, located in the Western Himalayas. The study also evaluates land-use transitions contributing to an increase in built-up areas. Our findings reveal a 162% increase in built-up areas, with the conversion of agricultural land to built-up areas being a prominent land-use transition. New built-up areas potentially face increased risks of landslides and flash floods due to their locations on steeper slopes and proximity to water streams, respectively. We discuss potential drivers of this urbanization trend and their impact on the mountain ecosystem.

In response to the widespread decline in ecosystem service value (ESV) caused by rapid industrialization and urbanization-driven land-use transitions in Coastal China—characterized by shrinking farmland and expanding built-up land and crystallized in the “core-city sprawl and surrounding-farmland encroachment” pattern—this study integrated land-use and socioeconomic data from 1980 to 2020. Employing the equivalent-factor method and Geodetector model, we quantified the spatiotemporal evolution of ESV and its driving mechanisms across the entire coastal region. The results show that (i) the total ESV experienced a fluctuating increase. (ii) Spatially, the ESV exhibited a “high in the south, low in the north, and higher inland than along the immediate coast” pattern, with mountain–hill belts and estuarine wetlands in the south forming high-value clusters, whereas the Bohai Rim in the north emerged as a low-value zone. (iii) Socioeconomic factors increasingly dominated the driving forces, while NDVI became the most influential natural factor; the interactions between the drivers consistently produced bi-factor enhancement effects. These findings provide a scientific basis for implementing the “Two-Mountains Theory” and optimizing coastal territorial spatial planning.

Aim: The Divjakë–Karavasta region, located along the central Albanian coast, represents one of the most dynamic Mediterranean landscapes, where human intervention has progressively reshaped natural ecosystems over the past two centuries. This study analyzed the long-term evolution of the Divjakë–Karavasta landscape from the early 19th century to the present, focusing on how natural and human-induced processes have shaped ecological and socio-economic systems. The aim is to assess the implications of these transformations for sustainable coastal. Methods: A diachronic and comparative analysis was conducted using historical topographic maps (Austrian, 1918; Italian, 1930s; Albanian, 1960s and 1980s), complemented by documentary sources, aerial imagery, and field observations. Geospatial interpretation was employed to delineate land-use transitions, the extent of wetland drainage, deforestation, settlement expansion, and post-1990 urban growth. The analysis integrates both qualitative and quantitative indicators of landscape modification to reconstruct the spatial and temporal dynamics of change. Results: Findings indicate a progressive transformation from a predominantly natural wetland ecosystem with minimal human impact to an intensively managed agricultural and settlement landscape. The most radical alterations occurred during the 1960s–1980s due to large-scale reclamation and collectivization projects, resulting in extensive wetland drainage, fragmentation of forest cover, soil salinization, and biodiversity loss. The post-1990 period introduced a new phase of unregulated land conversion and dispersed urban expansion, further compromising ecological stability. These cumulative changes have redefined the hydrological balance and reduced the resilience of the Divjakë–Karavasta ecosystem. Conclusion: The study concludes that the Divjakë–Karavasta landscape reflects a critical transition from natural to anthropogenic dominance, characterized by short-term agricultural gains but long-term ecological degradation. Recommendation: To restore ecological integrity and ensure long-term sustainability, local and national authorities should adopt an integrated coastal management plan that combines environmental restoration, climate adaptation, and spatial planning within the Divjakë–Karavasta region. This approach should prioritize wetland and buffer-zone restoration, reforestation, and strict regulation of construction and land use, while fostering active community participation and alignment with EU environmental and conservation frameworks to balance ecological preservation with sustainable regional development.

<p>Urbanization substantially restructures landscape composition, yet fine-scale patterns of vascular plant diversity along urban–natural gradients remain insufficiently examined, particularly in ecologically heterogeneous, rapidly transforming Anatolian cities. This study explores floristic diversity across an urban–rural continuum in Düzce, a mid-sized city in the Western Black Sea region of Turkey, using a stratified design encompassing 397 vegetation plots across five ecologically informed transects. Each transect captured distinct land-use and topographic transitions—including forest interfaces, industrial zones, major roads, elevational shifts, and riparian corridors. Shannon diversity (H′) analyses revealed consistent declines in transitional areas, in contrast to elevated and stable diversity in forests, riparian margins, and steep slopes. Unexpectedly high diversity was also recorded in select urban sites, influenced by habitat mosaics and microclimatic variability. Species composition was dominated by disturbance-tolerant, cosmopolitan taxa such as <em>Festuca rubra</em>, <em>Cynodon dactylon</em>, and <em>Agrostis stolonifera</em>, reflecting strong ecological filtering across the urban matrix. Additionally, the persistent occurrence of native trees such as <em>Tilia tomentosa</em> across both urban and natural zones suggests the functional adaptability of certain mesophytic species to diverse urban contexts, while <em>Fagus orientalis</em> remained confined to interior forest sections, indicating sensitivity to fragmentation and disturbance.</p>

To address the difficult problem of maintaining profitable and resilient agriculture under a changed climate, long-term prediction and planning are needed. One approach capable of helping with this endeavour is mathematical modelling and optimisation. Using a temporal framework, this paper outlines a spatio-temporal agricultural land use sequencer (STALS) model, where feasible climate-aware annual crop land uses are determined for a real-world case study region, the Murrumbidgee Irrigation Area in Australia. The results of this approach identified desirable transitions in land use and changes in the production system. The analysis revealed two differing possibilities of land use: one with a concentrated crop mix, the other more diverse. However, both suggest higher-value crops, such as horticultural species, will maximise regional economic benefit with comparable minimal water usage under climate change. To maintain regional agricultural economic benefit under reduced water availability and increased temperature, a transformation of land use is needed.

Urban growth models often prioritize environmental and accessibility factors while underestimating behavioral and functional dynamics. This study develops a POI-enhanced Cellular Automata (CA) framework to simulate urban expansion by incorporating three semantic indicators derived from Point-of-Interest (POI) data—density (PD), diversity (PDI), and functional centrality (FC). Taking Yan’an, China, as a case, the model integrates these indicators with terrain and infrastructure variables via logistic regression to estimate land-use transition probabilities. To ensure robustness, spatial block cross-validation was adopted to reduce spatial autocorrelation bias. Results show that the POI-based model outperforms the baseline in both Kappa and Figure of Merit metrics. High-density and mixed-function POI zones correspond with compact infill growth, while high-centrality zones predict decentralized expansion beyond administrative cores. These findings highlight how functional semantics sharpen spatial prediction and uncover latent behavioral demand. Policy implications include using POI-informed maps for adaptive zoning, ecological buffer protection, and growth hotspot management. The study contributes a transferable workflow for embedding behavioral logic into spatial simulation. However, limitations remain: the model relies on static POI data, omits vertical (3D) development, and lacks direct comparison with alternative models like Random Forest or SVM. Future research could explore dynamic POI trajectories, integrate 3D building forms, or adopt agent-based modeling for richer institutional representation. Overall, the approach enhances both the accuracy and interpretability of urban growth modeling, providing a flexible tool for planning in functionally evolving and ecologically constrained cities.

The acceleration of global environmental change has intensified the pace of land use and land cover change (LULCC) while increasing the uncertainty of its future development. Extracting information from past multi-period land-use transitions and scientifically identifying land-use transition patterns are essential for informing land-use decision-making. To this end, this study proposes a novel transition-level analytical framework-the Land Transition Intensity Spectrum (LTIS). The LTIS integrates absolute and relative transition intensities, gain and loss directions, and multiple temporal intervals. Through a quantitative approach, it identifies transitions that, across multiple periods, stably exhibit targeted tendencies in both absolute magnitude and relative proportion for the initial and final land use and land cover (LULC) classes. These transitions strongly affect the compositional structure of land use and should be prioritized in monitoring and governance. The LTIS was applied to LULC data from seven representative countries between 2000 and 2020, focusing on transitions among six major land classes to evaluate its utility. The results reveal that the LTIS effectively uncovers shared and divergent LULCC patterns across countries. Overall, the LTIS extends the analytical depth of conventional intensity analysis by integrating absolute and relative perspectives while enhancing the visualization and interpretability of land-use transitions.