Search Results (1,659)

Accurate quantification of wildland fuel consumption is essential for effective fire management in Northern European heathland ecosystems, yet traditional assessment methods remain spatially limited and labour-intensive. This study combined multitemporal UAV LiDAR with SLIC superpixel-based classification to directly measure fuel consumption following a prescribed burn in a Belgian heathland. Pre- and post-fire LiDAR surveys were conducted to capture vegetation height changes. Superpixel segmentation successfully classified three vegetation types (grassland, heather and trees with understory vegetation) with 97.8% accuracy. Fuel consumption analysis revealed remarkable differences between vegetation types, with heather (mean ± SD: 0.165 ± 0.102 m) exhibiting the highest consumption compared to grass (0.089 ± 0.088 m) and tree understory vegetation (0.091 ± 0.068 m). Statistical analysis confirmed the significant differences between all vegetation types (p-value < 0.001). This methodology provides quantitative evidence for developing vegetation-specific burning protocols by demonstrating the critical importance of both pre- and post-fire remote sensing data. The approach demonstrates the effectiveness of UAV-based multitemporal LiDAR for precise fuel consumption assessment in heathland fire management. Full article

Grassland aboveground biomass (AGB) serves as a critical indicator of ecosystem productivity and carbon cycling, playing a pivotal role in ecosystem functioning. The advances in hyperspectral and terrestrial Light Detection and Ranging (LiDAR) data have provided new opportunities for grassland AGB monitoring, but current research remains predominantly focused on data-driven machine learning models. The black-box nature of such approaches resulted in a lack of clear interpretation regarding the coupling relationships between these two data types in grassland AGB estimation. For grassland aboveground fresh biomass, the theoretical estimation can be decomposed into either the product of planar density (PD) and plot area or the product of stereoscopic density (SD) and grassland community volume. Based on this theory, our study developed a semi-mechanistic remote sensing model for grassland AGB estimation by integrating hyperspectral-derived biomass density with extracted structural parameters from terrestrial LiDAR. Initially, we built hyperspectral estimation models for both PD and SD of grassland fresh AGB using PLSR. Subsequently, by integrating the inversion results with grassland quadrat area and community volume measurements, respectively, we achieved quadrat-scale remote sensing estimation of grassland AGB. Finally, we conducted comparative accuracy assessments of both methods across different phenological stages to evaluate their performance differences. Our results demonstrated that SD, which incorporated structural features, could be more precisely estimated (R² = 0.90, nRMSE = 7.92%, Bias% = 0.01%) based on hyperspectral data compared to PD (R² = 0.79, nRMSE = 10.19%, Bias% = −7.25%), with significant differences observed in their respective responsive spectral bands. PD showed greater sensitivity to shortwave infrared regions, while SD exhibited stronger associations with visible, red-edge, and near-infrared bands. Although both methods achieved comparable overall AGB estimation accuracy (PD-based: R² = 0.79, nRMSE = 10.19%, Bias% = −7.25%; SD-based: R² = 0.82, nRMSE = 10.58%, Bias% = 1.86%), the SD-based approach effectively mitigated the underestimation of high biomass values caused by spectral saturation effects and also demonstrated superior and more stable performance across different growth periods (R² > 0.6). This work provided concrete physical meaning to the integration of hyperspectral and LiDAR data for grassland AGB monitoring and further suggested the potential of multi-source remote sensing data fusion in estimating grassland AGB. The findings offered theoretical foundations for developing large-scale grassland AGB monitoring models using airborne and spaceborne remote sensing platforms. Full article

As a critical ecological security node in North China, the Baiyangdian Basin underpins regional water resources, biodiversity conservation, and environmental risk mitigation. Its ecological integrity is fundamental to the sustainable development of the Beijing–Tianjin–Hebei (BTH) megaregion. This study leveraged Google Earth Engine (GEE) to quantify spatiotemporal ecosystem dynamics within the Baiyangdian watershed from 1990 to 2023, utilizing the Remote Sensing Ecological Index (RSEI). The primary drivers influencing the watershed’s ecological and environmental quality were subsequently analyzed. The results show that the ecological quality of the Baiyangdian Basin showed fluctuating changes from 1990 to 2023. Overall, the northwestern part of the Baiyangdian Basin improved significantly, while the southeastern part was slightly degraded, and the intensity of the change between different RSEI grades was low, mainly fluctuating between poor, medium, and good grades. Both anthropogenic and natural factors have high explanatory power for the ecological quality of the Baiyangdian watershed, and the land use type in particular is the main driver of changes in the RSEI area. The explanatory power of these factors was significantly enhanced by the interaction between them, especially the interaction between the land use type and other drivers. Within the drivers of the land use type, the cropland area, woodland area, shrub area, and grassland area have a significant influence. In summary, the area change in different land use types is the main factor influencing the ecological quality of the Baiyangdian watershed. This study has demonstrative value and implications for large-scale shallow lakes and wetlands, ecological barriers in rapidly urbanizing regions, the integrated management of cross-administrative watersheds, and the use of the GEE platform for long time-series and large-scale ecological monitoring and assessment. Full article

Ecosystem services play a vital role in human well-being, with land-use changes exerting substantial influence on ecosystem service value (ESV) and land-use carbon emissions (LUCEs). Understanding the spatio-temporal relationship and transition dynamics between ESV and LUCEs is essential for promoting high-quality ecological development aligned with the “dual carbon” objective. This study takes the Loess Plateau as the research object. Based on five-phase land-use data from 2000 to 2020, the ESV and LUCEs are calculated. Exploratory spatio-temporal data analysis is used to explore their spatio-temporal relationship and transition paths, and the quadrant model is introduced to analyze the transition patterns from the perspective of ecological quality. The results indicate the following: (1) From 2000 to 2020, the ESV of the Loess Plateau increased from CNY 579.032 billion to CNY 582.470 billion, with an overall increase of only 0.15%. Among the changes in land use, changes in forest and grassland significantly affected the ESV. (2) The LUCEs from land use on the Loess Plateau increased from 137.15 Mt to 458.43 Mt, with an average annual growth rate of 6.22%. Affected by industrialization and urbanization, the LUCEs showed significant spatial differences at the provincial and county scales. (3) There was a certain positive spatial correlation between ESV and LUCEs. The distribution of significantly correlated areas did not change significantly from 2000 to 2020, and the relationship characteristics were mainly characterized by Type IV transitions. (4) At the county scale, ESV and LUCEs exhibited temporal stability, with most counties situated in the general ecological category, indicating substantial potential for enhancing regional ecological quality. These research outcomes offer a foundational framework for devising tailored regional carbon emission reduction strategies. Full article

Climate change results from disruptions in Earth’s radiation energy balance. Radiative forcing is the dominant factor of climate change. Yet, most studies have focused on radiative effects within the calculated actual albedo, usually overlooking the angle effect of regions with large-scale and highly varied terrain. This study produced the actual albedo databases by using albedo retrieval look-up tables. And then we investigated the spatiotemporal variations in land surface albedo and its corresponding radiative effects in the Yellow River Basin from 2000 to 2022 using MODIS-derived reflectance data. We employed time-series, trend, and anomaly detection analyses alongside surface downward shortwave radiation measurements to quantify the radiative forcing induced by land-cover changes. Our key findings reveal that (i) the basin’s average surface albedo was 0.171, with observed values ranging from 0.058 to 0.289; the highest variability was noted in the Loess Plateau during winter—primarily due to snowfall and low temperatures; (ii) a notable declining trend in the annual average albedo was observed in conjunction with rising temperatures, with annual values fluctuating between 0.165 and 0.184 and monthly averages spanning 0.1595 to 0.1853; (iii) land-cover transitions exerted distinct radiative forcing effects: conversions from grassland, shrubland, and wetland to water bodies produced forcings of 2.657, 2.280, and 2.007 W/m², respectively, while shifts between barren land and cropland generated forcings of 4.315 and 2.696 W/m². In contrast, transitions from cropland to shrubland and from grassland to shrubland resulted in minimal forcing, and changes from impervious surfaces and forested areas to other cover types yielded negative forcing, thereby exerting a net cooling effect. These findings not only deepen our understanding of the interplay between land-cover transitions and radiative forcing within the Yellow River Basin but also offer robust scientific support for regional climate adaptation, ecological planning, and sustainable land use management. Full article

Effective nutrient management in grassland ecosystems is essential for maintaining soil nutrient balance and ensuring high forage productivity. A field experiment was conducted between 2022 and 2024 on a permanent dry meadow at the Experimental Station in Poznań-Strzeszyn, western Poland. The trial, established in autumn 2021, was carried out under production conditions on large plots (140 m² each). Plots were assigned to different fertilisation regimes, varying in both type and dosage. The treatments included an unfertilised control, three levels of annual mineral NPK fertilisation (NPK1, NPK2, NPK3), three levels of annually applied farmyard manure (FYM1, FYM2, FYM3), and three levels of mineral and organic fertilisers applied every two years (NPK1/FYM1, NPK2/FYM2, NPK3/FYM3). Throughout the study, botanical composition, annual dry matter yield (DMY), nitrogen (N), phosphorus (P), and potassium (K) content in the plant biomass were assessed. A simplified nutrient balance was calculated based on nutrient input from fertilisers and nutrient output with harvested yield. The average N balance across three years ranged from −12.17 kg N ha⁻¹ in control to +20.6 kg N ha⁻¹ in FYM3. For phosphorus, average balances ranged from −7.2 kg P ha⁻¹ in the control to +9.8 kg P ha⁻¹ in FYM3. In contrast, potassium balances were mostly negative: from −51.7 kg K ha⁻¹ in FYM1 to −7.4 kg K ha⁻¹ in NPK1. The most balanced nutrient budgets were observed under alternate NPK/FYM fertilisation, with moderate surpluses of N and P and a smaller K deficit compared to FYM applied alone. In contrast, inorganic and organic fertilisation applied separately resulted in greater nutrient surpluses or a pronounced potassium deficit. This study emphasises the importance of balanced nutrient management in permanent meadows, showing that moderate fertilisation strategies, such as alternating FYM and mineral NPK, can maintain productivity, and reduce environmental impacts. These findings provide a practical basis for developing sustainable grassland management practices under variable climatic conditions. Full article

This paper examines the characteristics of agriculture in High Nature Value farmlands (HNVf) in Poland and assesses their capacity to implement key environmental measures under the Common Agricultural Policy (CAP) 2023–2027. Using spatial and statistical analyses at the municipal level, the study compares agricultural structures, production types, participation in eco-schemes, organic farming and agri-environment-climate measures under the CAP 2023–2027. The delimitation of HNVf areas was based on the EU methodology, focusing on the extent of agricultural production and the environmental value of the surrounding landscape. The results indicate that HNVf areas are predominantly located in regions with challenging natural conditions, a high share of permanent grasslands, and limited capacity to diversify crop structures. Farms in these areas show lower participation in eco-schemes compared to more intensive farming regions, suggesting that current instruments may not fully align with the specific needs of low-intensity systems. In contrast, higher levels of engagement were observed in organic farming and agri-environment-climate measures in HNVf. These findings highlight the need for better-adapted CAP instruments that reflect the environmental and economic realities of HNVf areas. Enhancing support mechanisms for these regions is essential to safeguard biodiversity, promote sustainable land use, and maintain the socio-environmental functions of rural landscapes. Full article

Habitat and climate changes driven by human activities are altering the distribution of organisms globally. In South Korea, recent temperature increases have exceeded twice the global average, and habitats have markedly changed and shrunk due to urban development driven by population growth and economic expansion. Despite its high biodiversity and over 500 years of preservation, Gwangneung Forest in South Korea has experienced habitat alterations due to the urbanization of surrounding rural areas since the 1990s. In this study, we aimed to evaluate how butterfly communities respond to urbanization and climate change using long-term monitoring data (1998–2015) from the conserved Gwangneung Forest. We considered the thermal adaptation types (cold-, warm-, and moderately adapted species), habitat types (forest edge, forest inside, and grassland), diet breadth (monophagous, oligophagous, and polyphagous), and wingspan of butterflies. Linear regression analysis of the abundance trends for each species revealed that cold-adapted species experienced population declines, while warm-adapted species showed increases. Changes in butterfly abundance were associated with both thermal adaptation type and wingspan, with larger, more mobile species showing greater resistance to habitat loss in surrounding areas. To preserve butterfly diversity in Gwangneung Forest and across South Korea, it is crucial to conserve open green habitats—such as gardens, small arable lands, and grasslands—within urban areas, especially considering the impacts of climate change and habitat loss, which disproportionately affect smaller species with limited mobility. Full article

Vegetation–heat flux feedbacks have a great influence on ecosystems, but the interaction between them is still unclear. This is particularly critical in ecologically fragile areas, where plant growth is especially sensitive to land–atmosphere interactions that help plants withstand environmental pressures. To the causal relationship between vegetation and heat flux under different topographies on the Tibetan Plateau, we improved the Granger causality model to handle nonstationary scenarios, enabling us to uncover previously unknown interaction patterns between unstable vegetation change and heat fluxes. Further sensitivity analysis was performed to assess the strength of causal influences. The results showed that the sensible heat (SH) and latent heat (LH) fluxes were increasing at rates of 0.28 W·m⁻²·decade⁻¹ and 0.105 W·m⁻²·decade⁻¹, respectively. The interaction between them on vegetation change depends on terrains, at low elevations below 3000 m and high elevations of 5000–6000 m, SH and LH jointly regulate vegetation growth of shady and gentle to moderate slopes, predominantly involving dense grasslands, but the influence of SH is stronger. While at middle elevations of 3000–5000 m and on steep slopes, LH and vegetation of all types interact to form an intensive local energy cycle. Conversely, vegetation change also influences heat flux. Below 6000 m (excluding the 2000–3000 m), vegetation only regulates LH, and this influence appears largely independent of terrain, contributing to energy redistribution and water cycle maintenance in these regions. These interactions suggest that vegetation plays a central role in shaping energy distribution on the plateau, maintaining the water cycle, and regulating climate in alpine regions by regulating heat flux. Full article

Agricultural land consolidation (ALC) is a critical instrument for protecting the environment and expanding cropland. However, implementing different consolidation methods, scales, and technologies may have adverse effects on ecological and environmental factors. The ecological effects of ALC are evaluated in this investigation, with the Manas River Basin in China as the research object. Initially, the research examined the changes in land use that occurred during various periods of ALC in the basin using land cover data (CLCD). Secondly, an enhanced water benefit-based ecological index (SWBEI) for arid regions was developed using the Google Earth Engine (GEE) platform. The spatiotemporal variations in ecological environment quality (EEQ) during various ALC periods were analysed. Ultimately, the effects of a variety of factors on EEQ were disclosed. The research results show that: (1) The principal land-use types in the Manas River Basin are barren land, grassland, and cropland, with substantial fluctuations in area. Cropland area is increasing, with the majority being converted from grassland and desolate land. During the initial phase of farmland consolidation, the most rapid growth was observed, with expansion occurring both inward and outward from existing cropland. (2) The SWBEI outperforms the water benefit-based ecological index (WBEI) in arid regions. (3) The EEQ of the basin and cropland typically exhibits an “increasing–decreasing–increasing trend”, with deterioration predominantly occurring during early-stage ALC and a gradual improvement in EEQ during late-stage ALC. The Gobi Desert belt at the foothills of mountains and high-altitude frigid regions exhibit a deteriorating trend in the EEQ, whereas the oasis areas in the middle reaches of the basin exhibit an improving trend. (4) The most significant explanatory power for the basin’s EEQ is attributed to climate factors, followed by topographic factors, hydrological factors, and human factors. The influence of human factors and hydrological factors on the basin’s EEQ is increasing. The primary factors that influence the EEQ of a basin are the actual evapotranspiration, temperature, and elevation. The explanatory power of these two factors for the basin’s EEQ is augmented by their interaction. In the long term, ALC helps improve the EEQ of the basin and cropland. This study provides a reference for improving ALC methods and approaches, enhancing the ecological environment of river basins, and balancing agricultural production efficiency. Full article

Land use/cover (LUCC) change in arid oasis–desert ecotones has significant implications for spatial governance in ecologically fragile regions. To better capture the temporal and spatial complexity of land transitions, this study developed a vector tracing method by integrating time-series remote sensing data with vector-based transfer pathways. Analysis of northern Oman from 1995 to 2020 revealed the following: (1) Arable land and impervious surfaces expanded from 0.51% to 1.09% and from 0.31% to 0.98%, respectively, while sand declined from 99.03% to 97.01%. Spatially, arable land was concentrated in piedmont irrigation zones, impervious surfaces near coastal cities, and shrubland and grassland along the Al-Hajar Mountains, forming a complementary land use mosaic. (2) Human activities were the dominant driver, with typical one-way chains accounting for 69.76% of total change. Sand was mainly transformed into arable land (7_C1, 7_D1, 7_E1; where the first part denotes the original type, the letter denotes the year of change, and the last digit denotes the new type), impervious surfaces (7_C6, 7_D6, 7_E6), and shrubland (7_E4). (3) Water scarcity and an arid climate remained primary constraints, manifested in typical reciprocating chains in the oasis–desert interface (7_D1_E7, 7_A1_B7, 7_C1_D7) and in the arid vegetation zone along the Al-Hajar Mountain foothills (7_D3_E7, 7_C3_D7), together accounting for 24.50% of total change. (4) The region exhibited coordinated transitions among oasis, urban, and ecological land, avoiding the common conflict of cropland loss to urbanization. During the study period, transitions among arable land, impervious surfaces, forest, shrubland, and wetland were rare (Type 16: 3.31%, Type 82: 2.89%, Type 12: 0.04%, Type 18: 0.01%). The case of northern Oman provides a valuable reference for collaborative spatial governance in ecologically fragile arid zones. Future research should integrate socio-economic drivers, climate change projections, and higher-temporal-resolution data to enhance the applicability of the chain-spectrum method in other arid regions. Full article

Dominant species form species-specific fine-scale vegetation matrices in grasslands that regulate community dynamics, diversity and ecosystem functioning. The structure of these dynamic microscale landscapes was analyzed and compared between primary and secondary plant communities. We explored fine-scale monitoring data along permanent transects over seven consecutive years. Spatial and temporal patterns of dominant grass species (Festuca valesiaca, Alopecurus pratensis and Poa angustifolia) were analyzed using information theory models. These matrix-forming species showed high spatiotemporal variability in all grasslands. However, consistent differences were found between primary and secondary grasslands in the spatial and temporal organization of the vegetation matrix. Alopecurus pratensis and Poa angustifolia had coarse-scale patchiness with stronger aggregation in secondary grasslands. The spatial patterns of Festuca valesiaca were nearly random in both types of grasslands. Strong associations were observed among the spatial patterns of each species across years, with a stronger dependence in secondary grasslands. In contrast, the rate of fine-scale dynamics was higher in primary grasslands. The complexity of microhabitats within the matrix was higher in primary grasslands, often involving two to three dominant species, while, in secondary grasslands, patches formed by a single dominant species were more frequent. In the spatial variability of small-scale subordinate species richness, significant, temporally consistent differences were found. Higher variability in secondary grasslands suggests stronger and more spatially variable microhabitat filtering. We recommend that grassland management and restoration practices be guided by preliminary information on the spatial organization of primary grasslands. Enhancing the complexity of the matrix formed by dominant species can further improve the condition of secondary grasslands. Full article

Mountainous regions with complex terrain often generate mixed pixels, reducing the accuracy of land use classification. This study evaluates the applicability and performance of eight commonly used Land Use Products (LUPs) with resolutions from 10 m to 1000 m in a typical mountainous area of the Wumeng Mountains, using manually vectorized high-resolution imagery as reference data. The spatial patterns of classification inconsistency and topographic influences were systematically analyzed. Results show the following: (1) All LUPs underestimate Cropland, Forest, Built-up areas, and Waters, while overestimating Grassland. Most products perform poorly, with an Overall Accuracy (OA) below 0.7. (2) Classification performance varies by land cover type and location. In complex terrains, high fragmentation causes mixed pixels, leading to inconsistency. (3) XGBoost and SHAP analyses indicate elevation and Terrain Surface Complexity as dominant factors. Accuracy increases with elevation and is higher on shady than on sunny slopes. Greater surface complexity reduces performance. (4) Spatial resolution alone does not determine performance—algorithm design, sample distribution, and data fusion are critical. All eight LUPs show poor applicability in mountainous regions. Future research should emphasize terrain-stratified sample balancing, terrain-aware algorithms, and strategies to mitigate mixed pixel effects. Full article

The ecological interface between grasslands and farmlands forms a critical landscape component, significantly contributing to the stability and functioning of ecosystems within the agro-pastoral transition zone of northern China. Nevertheless, the variation patterns and interactions between soil physicochemical attributes and microbial community diversity at this interface remain poorly understood. In this study, we investigated nine sites located within 50 m of the grassland–farmland boundary in the Songnen Plain, northeastern China. We assessed the soil’s physicochemical properties and the composition of bacterial and fungal communities across these sites. Results indicated a declining gradient in soil physicochemical characteristics from grassland to farmland, except for pH and total phosphorus (TP). The composition of bacterial and fungal communities differed notably in response to contrasting land-use types across the ecological interface. Soil environmental variables were closely aligned with shifts observed in bacterial and fungal assemblages. Concentrations of total nitrogen (TN), available phosphorus (AP), alkali-hydrolyzable nitrogen (AN), and available potassium (AK) exhibited inverse correlations with both bacterial and fungal populations. Alterations in microbial community composition were significantly linked to TN, TP, total potassium (TK), AN, AP, AK, and soil pH levels. Variability in soil properties, as well as microbial biomass and diversity, was evident across the grassland–cropland boundary. Long-term utilization and conversion of grassland into cultivated land altered the soil’s physicochemical environment, thereby indirectly shaping the structure of microbial communities, including both bacteria and fungi. These findings provide a valuable basis for understanding the ecological implications of land-use transitions and inform microbial-based indicators for assessing soil health in agro-pastoral ecotones. Full article

Soil reflects ecosystem processes and is influenced by gradual biospheric changes, which can affect its biotic components. In fairy rings, soil morphology, physicochemical properties, and biota are interconnected within a shared environmental space. In La Bertolina grasslands, while fungal and bacterial genomics have been investigated, the micromorphological soil effects of these rings have not. This study micromorphologically analyzed thin sections of three fairy rings at four zones: the ring center, the zone of peak growth in 2013 (R13), the predicted growth zone for 2019 (R19), and outside the ring. From each zone, two thin soil sections were prepared, totaling 24 samples. Fungal structures were exhaustively described according to morphological criteria following reference by multiple authors. The soil was a calcareous, loamy Regosol, and showed moderately developed crumb or laminar microstructures. Nine types of fungal structures were identified, consistent with genomic findings in the zone. Although fungal abundance did not vary across zones, mesofauna droppings were more frequent in R13 and R19, which was related to higher nutrient or water availability due to the fungal activity. Regarding the groundmass of the topsoil, neither the composition nor the microstructure of the surface horizons varied according to the moment of appearance of the ring at the sampled points. Full article