Search Results (279)

In the rapid urbanization process, ecological spaces are continuously encroached upon, leading to an increase in landscape fragmentation. This, in turn, results in a series of issues, such as weakened ecological connectivity and an imbalance in the supply and demand of ecosystem services. Green infrastructure serves a variety of ecosystem functions, and constructing and optimizing ecological networks based on green infrastructure is a key approach to enhancing landscape connectivity and mitigating the negative effects of urbanization. This study takes the central urban area of Fuzhou as a case study, innovatively combining the ecological network construction with supply–demand assessments of green infrastructure. It identifies ecological nodes and priority optimization zones. Results indicate that green infrastructure supply exhibits a pattern of “low in the central-eastern areas and high in the northern–southern areas,” while demand shows the opposite trend, revealing significant spatial mismatch between the two. The study identifies 7 key optimization areas, 29 ecological sources, 35 ecological corridors, and 61 ecological nodes. These are classified into core, important, and general levels based on centrality indices, and the ecological elements are finally overlapped to form an ecological network. This research provides practical insights for optimizing green infrastructure. Full article

Wildfires are among the most severe disturbances in Mediterranean ecosystems, altering vegetation structure, soil properties, and hydrological functioning. Understanding post-fire hydrological dynamics is crucial for predicting flood and erosion risks and vegetation restoration in fire-prone regions. This study investigates the hydrological responses of Mediterranean watersheds following a wildfire event by integrating WiMMed (Watershed Integrated Management in Mediterranean Environments), a distributed, physically based hydrological model, with high-resolution vegetation data derived from LiDAR and Landsat imagery. A Priority Post-Fire Restoration Index (PPRI) was calculated as the weighted sum of the six parameters runoff (mm), flow accumulation (mm), distance to drainage network (m), slope (%), erodibility (K), lithology, and LiDAR index under a sediment reduction and runoff peak reduction scenario. The post-fire hydrological processes modeled with WiMMed described the dynamics of surface runoff and soil moisture redistribution across the upper soil layers after fire, and their gradual attenuation with vegetation regrowth. The spatial distribution of the PPRI identified specific zones within the burned watershed that require urgent restoration measures (10% and 4.55% under sediment reduction and peak reduction scenarios, respectively). The combined use of process-based modeling and remote sensing offers valuable insights into watershed-scale hydrological resilience and supports the design of post-fire restoration strategies in Mediterranean landscapes. Full article

Mountain forests play a key role in buffering local climate, yet their climate sensitivity is seldom mapped in a way that is directly usable for spatial planning. This study investigates how phenological thermal and vegetation variability are organized within the forested landscape of Namyangju, a mountainous region in central Korea, and derives spatial indicators of forest climate sensitivity. Using monthly, cloud-screened Landsat-8/9 land surface temperature (LST) and normalized difference vegetation index (NDVI) images over a recent multi-year period, we calculated phenological coefficients of variation for 34,123 forest grid cells and applied local clustering analysis to identify belts of high and low variability. Forest areas where LST and NDVI variability simultaneously occupied the upper tail of their distributions (top 5%/10%/20%) were interpreted as climate-sensitivity hotspots, whereas co-located coldspots were treated as microclimatic refugia. Across the mountainous terrain, sensitivity hotspots formed continuous belts along high-elevation ridges and steep, dissected slopes, while coldspots were concentrated in sheltered valley floors. Notably, the most sensitive belts were dominated by high-elevation conifer stands, despite the limited seasonal fluctuation typically expected in evergreen canopies. This pattern suggests that elevation strongly amplifies the coupling between thermal responsiveness and vegetation health, whereas valley-bottom forests act as stabilizers that maintain comparatively constant microclimatic and phenological conditions. We refer to these patterns as “forest climate-sensitivity belts,” which translate satellite observations into spatially explicit information on where climate-buffering functions are most vulnerable or resilient. Incorporating climate-sensitivity belts into forest plans and adaptation strategies can guide elevation-aware species selection in new afforestation, targeted restoration and fuel-load management in upland sensitivity zones, and the protection of valley refugia that support biodiversity, thermal buffering, and hydrological regulation. Because the framework relies on standard satellite products and transparent calculations, it can be updated as new imagery becomes available and transferred to other seasonal, mountainous regions, providing a practical basis for climate-resilient forest planning. Full article

The study examines the recent transformation of traditional agricultural landscapes in the transition zone between Sierra de las Nieves and the Western Costa del Sol (Andalusia, Spain), one of the European regions where urban development pressure has reached its peak in replacing agricultural land with residential and tourism uses. Through a diachronic analysis of historical orthophotos (1956–2025), statistical sources (Agricultural Census, SIGPAC), and fieldwork, land-use changes and their impact on ecological functionality and territorial resilience are quantified. Results reveal a widespread loss of agricultural land—exceeding 68% overall—particularly severe in Benahavís, where more than 70% of farmland has disappeared, largely converted to urban areas. In contrast, in Istán and Ojén, the predominant trend is the renaturalization of abandoned agricultural land. These dynamics illustrate a coastal–inland territorial model that epitomizes the Mediterranean “territorial consumption” process, in which tourism-driven urbanization fragments traditional agroforestry mosaics. The study concludes that, despite their regression, traditional agricultural landscapes continue to play a key role in water regulation, soil conservation, and wildfire risk mitigation. Their restoration and maintenance are proposed as a replicable strategy for climate change adaptation and for reconciling territorial sustainability with economic development in other Mediterranean regions under intense urban pressure. Full article

Historical irrigation districts (HIDs) are integrated systems of natural and cultural assets, with cultivated land providing critical functions such as food security, environmental conservation, and cultural inheritance. This study presents a research framework for evaluating multifunctional potential, performance, and geographical matching along the “potential-performance” dimensions using analytical tools such as SPSS26.0, ArcGIS pro3.5.2, GeoDa1.22, InVEST3.13, and bivariate spatial autocorrelation. We use Mulanbei HID in China as a case study because of its thousand-year irrigation history and unique location at the intersection of coastal urban and rural communities. The results show the following: (1) In the Mulanbei HID, multifunctional cultivated land exhibits functions in the following order: producing functions, ecological functions, landscape–cultural functions, and social functions. The production function has a homogenous distribution characterized by high values. The ecological function, on the other hand, is distinguished by high-value clusters that decrease significantly as building land approaches its periphery. Social and landscape–cultural roles continue to be undervalued, with high-value places isolated on metropolitan margins. (2) In terms of matching multifunctional potential and performance, in the High-Potential–High-Performance cluster, production and ecological functions account for 19% and 20%, respectively, while in the High-Potential–Low-Performance cluster, social and landscape–cultural functions account for 33% and 27%. The Low-Potential–Low-Performance cluster has 4% production, 4% ecological, 10% social, and 13% landscape–cultural functions, but all four functions are less than 4% in the Low-Potential–High-Performance cluster. These findings provide a scientific foundation for improving cultivated land zoning and governance with a focus on heritage protection. Full article

This paper proposes an innovative methodological framework for integrating Cultural Ecosystem Services (CES) into landscape planning, with the aim of enhancing the conservation and adaptive management of rural historical landscapes. Grounded in the principles of the European Landscape Convention and the recent Nature Restoration Law, the study advocates for a shift from prescriptive and sectoral approaches toward performance-based and ecosystem-oriented models. The research focuses on the Marche Region (Italy), where the historical landscape shaped by the mezzadria (sharecropping) system provides a representative case for testing the proposed methodology. Six spatial layers have been selected as ecosystem-based indicators to identify new potential landscape CES’ hotspots as agricultural landscape high-value areas, and to redefine protection and management strategies. The analysis integrates historical, ecological, and cultural dimensions to construct a spatially explicit value matrix, supporting the definition of differentiated management zones. Results reveal the persistence of high landscape and ecosystem values in mid- and upper-hill areas, contrasted by the progressive loss of structural and functional diversity in lowland and peri-urban contexts. The findings highlight the need for more adaptive and flexible planning models, capable of incorporating nature-based actions, climate-smart agriculture, and performance-oriented evaluation criteria. The proposed approach demonstrates potential for replicability and policy integration, providing a decision-support framework to align landscape planning with rural development strategies and climate adaptation objectives. Despite limitations related to data availability and model simplification, the methodology contributes to the ongoing paradigm shift toward dynamic, evidence-based, and transdisciplinary landscape governance across Mediterranean regions. Full article

In recent years, European cities have experienced rapid changes in their functional and spatial organisation, which have affected, among others, the natural environment, the economy and society. The intensive and often uncontrolled growth of residential development associated with suburbanisation significantly impacts areas located around urban areas. Growing investment pressures usually lead to the transformation of rural and naturally valuable areas, altering their character and functions. Solving these problems requires developing a method to determine the main directions and intensity of land use changes in the context of urbanisation pressures and sustainable spatial development. This article presents the results of a spatiotemporal analysis of the dynamics of built-up area development in rural and suburban zones, utilising Geographic Information Systems (GIS) technology. The study focused on the expansion of single- and multi-family housing around the city of Białystok, Poland, between 1997 and 2022. The analysis was based on spatial data, including available orthomosaics and cadastral data from the Topographic Objects Database (BDOT10k). The GIS-based analysis covered an area of nearly 2000 km² and included methods for change detection, analysis, and land cover classification. The results indicated a marked intensification in landscape transformations, particularly in transition zones between rural and urban areas. At the same time, forests and protected zones significantly influenced the direction and pace of development, acting as natural barriers limiting spatial expansion. The results indicate the need to consider environmental factors (e.g., protected areas and forests) in spatial planning processes and sustainable development policies. The study confirms the high usefulness of GIS tools in monitoring and forecasting spatial change at both the local and regional scales. This research also contributes to the discussion on urbanisation, its characteristics, causes, and consequences, and highlights the role of green spaces in limiting sprawl. Full article

Woody encroachment (WE) refers to the expansion of woody vegetation, particularly scrubs, into grasslands, altering ecosystem structure, function, and vegetation phenology. WE is especially pronounced in arid and semi-arid regions, where climate variability, land use, and ecological resilience interact strongly. Even though long-term monitoring of these dynamics in protected areas is essential to understanding landscape change and guiding conservation strategies, a few studies address this. The Flora and Fauna Protection Area (FFPA) Bavispe, a sky island in northwestern Mexico, provides an ideal setting to examine WE. Using remote sensing, we analyzed 30 years of land cover change (Landsat 5 TM and Landsat 8 OLI) in two reserve zones, Los Ajos and La Madera, and their 5 km buffer areas. Additionally, NDVI-based regressions (MODIS MOD13Q1) were applied to assess phenological responses across vegetation types. Classifications showed high accuracy (Kappa > 0.75) and revealed notable woody expansion: 960 ha of oak forest and 1322 ha of scrubland gained in Los Ajos, and 1420 ha of scrubland in La Madera. Grasslands declined by 2234 ha in Los Ajos and 1486 ha in La Madera, with stronger trends in surrounding buffers. Phenologically, the onset of the growing season was delayed by ~2 days per year in Los Ajos and ~3 days in La Madera. A generalized increment of woody vegetation in the region and the observed change in phenophases in selected land cover types indicated a shift in regional drivers (human or other ecological state factor) related to land cover distribution. Full article

Amid climate change and land-use transformation, the scientific identification of high-quality arable land reserves is critical for safeguarding both cropland quantity and quality. Conventional approaches, largely based on spatial autocorrelation and heterogeneity theories, inadequately capture the multi-scale integration of ecological functions and carbon cycling, particularly in ecologically high-risk areas where systematic identification and mechanism analysis are lacking. To address these challenges, this study introduces a geographically similar “grain-carbon” synergistic framework, paired with a “bidirectional optimization” strategy (negative elimination + positive selection), to overcome the shortcomings of traditional methods and mitigate grain–carbon trade-offs in high-risk areas. Using land-use data from Yunnan’s mountainous areas (2000–2020), integrated with InVEST-PLUS model outputs, multi-source remote sensing, and carbon pool datasets, we developed a dynamic land-use–carbon storage simulation framework under four policy scenarios: natural development, urban expansion, arable land protection, and ecological conservation. High-quality arable lands were identified through a geographic similarity analysis with the Geo detector, incorporating ecological vulnerability and landscape risk indices to delineate priority high-risk zones. Carbon storage degradation trends and land-use pressures were further considered to identify optimal areas for cropland-to-forest conversion, facilitating the implementation of the bidirectional optimization strategy. Multi-scenario simulations revealed an increase of 454.33 km² in high-quality arable land, with the optimized scenario achieving a maximum carbon storage gain of 23.54 × 10⁶ t, reversing carbon loss trends and enhancing both farmland protection and carbon sequestration. These findings validate the framework’s effectiveness, overcoming limitations of traditional methods and providing a robust strategy for coordinated optimization of carbon storage and arable land conservation in ecologically high-risk regions, with implications for regional carbon neutrality and food security. Full article

To clarify the multifunctional supply–demand relationship of cultivated land in the Yellow River Basin of Henan Province, and to provide decision-making support for strengthening cultivated land protection and promoting sustainable agricultural and rural utilisation within this basin, this study employs the entropy value method, hierarchical demand theory, and geographically weighted regression (GWR) models. Analyses were conducted at three scales—functional zoning, municipal, and county—to reveal the spatiotemporal evolution of supply and demand for the productive, ecological, social, and landscape functions of cultivated land from 2013 to 2023. This comprehensive assessment evaluates the supply and demand levels of multifunctional cultivated land within the study area and analyses the risks associated with shortages in multifunctional supply and demand. Results indicate: A significant spatial negative correlation exists between the supply and demand levels of multifunctional agricultural land in the Yellow River Basin of Henan Province. The supply level was in the range of [0.08–0.65], exhibiting an overall slight decreasing trend and a spatial pattern of higher values in the east and lower values in the west. The demand level was in the range of [0.11–0.82], showing an overall increasing trend and a spatial pattern of higher values at both ends and lower values in the middle. Between 2013 and 2023, the severity of multifunctional supply–demand scarcity risk gradually improved, exhibiting an overall spatial distribution pattern characterised by scarcity in core and expansion zones, surplus in coordination zones. Risk severity values ranged from −0.08 to 0.02 in core zones, 0.03 to 0.11 in expansion zones, and 0.08 to 0.16 in coordination zones. To optimise the multifunctional supply–demand structure of cultivated land in Henan’s Yellow River Basin, high-risk areas require targeted management and optimisation to mitigate supply–demand risks. The balance between multifunctional supply and demand for cultivated land should be achieved through tailored approaches, such as standardising cross-regional allocation of multifunctional cultivated land resources and establishing a multi-scale, integrated compensation mechanism for protecting cultivated land functions. Full article

This study investigates the changes and driving mechanisms of agritourism landscapes in mountainous regions of Southwest China, providing a scientific basis for sustainable landscape management. We analyzed Hanyuan County (2013–2023) using remote images, POI data, terrain niche index, distribution index, landscape transition matrix, and logistic regression model from a landscape function perspective. These analyses reveal that the landscape pattern maintains overall stability with local fluctuations, with ecologically oriented landscapes being consistently dominant (>76% coverage). The primary conversion direction of development-potential landscapes shifted from ecological to agricultural dominance after 2018. All landscape types have shown more distinct distribution advantages in the fifth-level terrain gradient, with intensified fluctuations in low-gradient areas after 2018. Location factors were the most common driving force, but their effects differ: production-oriented landscapes shifted from location–climate correlation to location–socioeconomic–terrain correlation; living-oriented landscapes remain influenced by slope and location accessibility; ecological-oriented landscapes shifted from a location–climate correlation to location–tourism correlation; development-potential landscapes were positively influenced by multiple factors. This study suggests implementing zoned management based on functions and terrain gradients through policy guidance and technological intervention. The findings of this study can provide a reference for the comprehensive revitalization of rural areas and the sustainable development of landscapes in similar areas. Full article

Ecological restoration in degraded landscapes requires understanding the factors driving ecosystem function. We ask the central question: Do microtopography and plant functional traits control water-carbon coupling efficiency (WCCI) in mining-affected grasslands? We developed a novel, decoupled WCCI metric balancing water-use efficiency (1/SLA) and carbon-stock potential (Height + Foliage Cover). We hypothesized that (1) microhabitats with severe environmental filters (e.g., drought, erosion) would exhibit the lowest WCCI, and (2) this function could be optimized by assembling species that balance these two distinct trait strategies. Our objectives were to: (i) quantify the new WCCI across five microhabitat zones (A–E); (ii) assess how soil filters shape existing community functions; and (iii) identify optimized, zone-specific species assemblages using a dual-filter CATS model that maximizes WCCI. Results show significant variability in WCCI. The most degraded zones, A (arid) and B (high erosion), exhibited the lowest functional performance (mean WCCI = 0.029 and 0.078), supporting our first hypothesis. The dual-filter CATS model, constrained by abiotic targets (Tolerance = 10%) and a diversity cap (Max Abundance = 30%), successfully generated distinct, functionally tailored species assemblages for each zone. For instance, the optimized community for arid Zone A included the drought-adapted grass Stipa capillata (15.9%), while the resource-rich Zone D was recommended Medicago lupulina (12.7%). Conclusion: These findings confirm that a “one-size-fits-all” approach is insufficient. We demonstrate the necessity of a trait-based, microhabitat-specific framework to move beyond taxonomic mimicry and truly optimize biogeochemical functions in restoration. Full article

Soil erosion poses a significant threat to the sustainability of land systems in karst mountainous regions, where steep slopes, shallow soils, and intensive human activities exacerbate land degradation, undermining both the productive functions and ecological services of land resources. This study evaluated soil erosion susceptibility in the karst-dominated Qingshui River watershed, Southwest China, and identified key drivers of land degradation to support targeted land management strategies. Four machine learning models, BPANN, BRTs, RF, and SVR were trained using twelve geo-environmental variables representing lithological, topographic, pedological, hydrological, and anthropogenic factors. Variable importance analysis revealed that annual precipitation, land use type, distance to roads, slope, and aspect consistently had the greatest influence on soil erosion patterns. Model performance assessment indicated that BRTs achieved the highest predictive accuracy (RMSE = 0.161, MAE = 0.056), followed by RF, BPANN, and SVR. Spatial susceptibility maps showed that high and very high erosion risk zones were mainly concentrated in the central and southeastern areas with steep slopes and exposed carbonate rocks, while low-risk zones were located in flatter, vegetated southwestern regions. These results confirm that hydrological conditions, topography, and anthropogenic activities are the primary drivers of soil erosion in karst landscapes. Importantly, the findings provide actionable insights for land and landscape management—such as optimizing land use, restoring vegetation on steep slopes, and regulating human activities in sensitive areas—to mitigate erosion, preserve land quality, and enhance the sustainability of karst land systems. Full article

Biodiversity maintenance function (BMF) denotes the capacity of ecosystems to sustain genetic, species, ecosystem, and landscape diversity. Assessing the spatial distribution and underlying drivers of BMF at the regional scale is essential for biodiversity management. However, research on the socio-ecological drivers of BMF from a geographical perspective remains scarce. Therefore, this study developed an integrated assessment framework encompassing climatic factors, species richness, vegetation status, ecosystem protection, and anthropogenic disturbance. We analyzed the BMF spatial patterns across Liaoning Province, China, and identified the dominant drivers and their spatial heterogeneity using multi-scale geographically weighted regression and geographical detector. The results show that (1) the eastern/western mountainous regions and Liaohe River estuary are critical BMF zones for prioritized conservation; (2) BMF spatial variation is mainly shaped by precipitation, temperature, slope, and forestland/farmland proportion, with factor interactions amplifying their impacts; (3) drivers show distinct spatial heterogeneity. Specifically, precipitation, slope, and NDVI exert homogeneous effects, whereas elevation, temperature, farmland/wetland proportion, and GDP exhibit pronounced heterogeneity. Natural factors generally exert positive effects, while the farmland/urban proportion tends to exert negative impacts—for example, farmland’s negative influence is stronger in the west, whereas the forestland and temperature exert more positive effects in the east. The results enhance the methodological framework for elucidating the spatial relationships between BMF and drivers, providing a scientific basis for biodiversity conservation and ecosystem management in Liaoning Province and similar regions. Full article

Landscape fragmentation is a dynamic process with multiple effects. In addition to reducing the area of priority ecosystems such as mangroves, it also generates alterations in ecological functions and environmental processes, with significant socioeconomic and ecological consequences. The objective of this research was to determine the impact of anthropic development on landscape fragmentation within the Environmental System (ES) that includes the Arroyo Moreno Ecological Reserve (REAM) and the Tembladeras-Laguna Olmeca Ecological Reserve (RETLO), located in central Veracruz Mexico. Fragstats V4.3 Beta software was used to analyze landscape metrics at the patch, class, and landscape levels, using nine indicator metrics for assessing fragmentation. The analysis of the metrics at the three levels showed a reduction in the total area for some classes such as Mangrove (MG), Water Bodies (WB), and Agricultural and Livestock (AL). Class-level metrics such as total area, percentage of landscape, and number of patches showed greater differences for some classes between 2001 and 2023. However, some values increased in 2015. However, this research is considered the first study conducted in the area to comprehensively use a set of landscape metrics at three organizational levels, offering a more accurate description of the status of priority ecosystems (RAMSAR sites) such as the wetlands of the coastal zone of Veracruz. It also demonstrated the importance of the constantly expanding anthropic development in the study area over the last 20 years and the potential pressure it exerts on biodiversity conservation sites such as wetlands. Full article