Search Results (485)

An in-depth understanding of the spatiotemporal heterogeneity of ecosystem service (ES) trade-offs and synergies, along with their driving factors, is crucial for formulating key ecological restoration strategies and effectively allocating ecological environmental resources in the Hulunbuir region. This study employed an integrated analytical approach combining the InVEST model, ArcGIS geospatial processing, R software environment, and Optimal Parameter Geographical Detector (OPGD). The spatiotemporal patterns and driving factors of the interaction of four major ES functions in Hulunbuir area from 2000 to 2020 were studied. The research findings are as follows: (1) carbon storage (CS) and soil conservation (SC) services in the Hulunbuir region mainly show a distribution pattern of high values in the central and northeast areas, with low values in the west and southeast. Water yield (WY) exhibits a distribution pattern characterized by high values in the central–western transition zone and southeast and low values in the west. For forage supply (FS), the overall pattern is higher in the west and lower in the east. (2) The trade-off relationships between CS and WY, CS and SC, and SC and WY are primarily concentrated in the western part of Hulunbuir, while the synergistic relationships are mainly observed in the central and eastern regions. In contrast, the trade-off relationships between CS and FS, as well as FS and WY, are predominantly located in the central and eastern parts of Hulunbuir, with the intensity of these trade-offs steadily increasing. The trade-off relationship between SC and FS is almost widespread throughout HulunBuir. (3) Fractional vegetation cover, mean annual precipitation, and land use type were the primary drivers affecting ESs. Among these factors, fractional vegetation cover demonstrates the highest explanatory power, with a q-value between 0.6 and 0.9. The slope and population density exhibit relatively weak explanatory power, with q-values ranging from 0.001 to 0.2. (4) The interactions between factors have a greater impact on the inter-relationships of ESs in the Hulunbuir region than individual factors alone. The research findings have facilitated the optimization and sustainable development of regional ES, providing a foundation for ecological conservation and restoration in Hulunbuir. Full article

The spatial variation of forest ecosystem services at regional scales remains poorly understood, and few studies have explicitly analyzed how ecosystem services are distributed across different forest management types. This study assessed the spatial overlap between forest management types and ecosystem service hotspots in the Southeastern United States (SEUS) and the Pacific Northwest (PNW) forests. We used the InVEST suite of tools and GIS to quantify carbon storage and water yield. Carbon storage was estimated, stratified by forest group and age class, and literature-based biomass pool values were applied. Average annual water yield and its temporal changes (2001–2020) were modeled using the annual water yield model, incorporating precipitation, potential evapotranspiration, vegetation type, and soil characteristics. Ecosystem service outputs were classified to identify hotspot zones (top 20%) and to evaluate the synergies and tradeoffs between these services. Hotspots were then overlaid with forest management maps to examine their distribution across management types. We found that only 2% of the SEUS and 11% of the PNW region were simultaneous hotspots for both services. In the SEUS, ecological and preservation forest management types showed higher efficiency in hotspot allocation, while in PNW, production forestry contributed relatively more to hotspot areas. These findings offer valuable insights for decision-makers and forest managers seeking to preserve the multiple benefits that forests provide at regional scales. Full article

Situated in the southern hilly-mountain belt of China’s “Three Zones and Four Belts Strategy”, Gannan region is a critical ecological shelter belt for the Ganjiang River. Decades of intensive mineral extraction and irrational agricultural development have rendered it into an ecologically fragile area. Consequently, multiple restoration initiatives have been implemented in the region over recent decades. However, it remains unclear how relationships among ecosystem services have evolved under these interventions and how future ecosystem management should be optimized based on these changes. Thus, in this study, we simulated and assessed the spatiotemporal dynamics of five key ESs in Gannan region from 1990 to 2020. Through integrated correlation, clustering, and redundancy analyses, we quantified ES interactions, tracked the evolution of ecosystem service bundles (ESBs), and identified their socio-ecological drivers. Despite a 31% decline in water yield, ecological restoration initiatives drove substantial improvements in key regulating services: carbon storage increased by 6.9 × 10¹² gC while soil conservation rose by 4.8 × 10⁸ t. Concurrently, regional habitat quality surged by 45% in mean scores, and food production increased by 2.1 × 10⁵ t. Critically, synergistic relationships between habitat quality, soil retention, and carbon storage were progressively strengthened, whereas trade-offs between food production and habitat quality intensified. Further analysis revealed that four distinct ESBs—the Agricultural Production Bundle (APB), Urban Development Bundle (UDB), Eco-Agriculture Transition Bundle (ETB), and Ecological Protection Bundle (EPB)—were shaped by slope, forest cover ratio, population density, and GDP. Notably, 38% of the ETB transformed into the EPB, with frequent spatial interactions observed between the APB and UDB. These findings underscore that future ecological restoration and conservation efforts should implement coordinated, multi-service management mechanisms. Full article

Elucidating the trade-offs and synergies among ecosystem services is crucial for effective ecosystem management and the promotion of sustainable development in specific regions. The Hexi Corridor, a vital agricultural hub in Northwest China, is instrumental in both ecological conservation and socioeconomic advancement throughout the area. Utilizing an integrated “water–soil–carbon–grain” framework, this study conducted a quantitative assessment of four essential ecosystem services within the Hexi Corridor from 2000 to 2020: water yield, soil conservation, vegetation carbon sequestration, and grain production. Our research thoroughly explores the equilibrium and synergistic interactions between grain production and other ecosystem services, while also exploring potential strategies to boost grain yields through the precise management of these services. The insights garnered are invaluable for strategic regional development and will contribute to the revitalization efforts in Northwest China. Key findings include the following: (1) between 2000 and 2020, grain production exhibited a steady increase, alongside rising trends in water yields, soil conservation, and carbon sequestration, all of which demonstrated significant synergies with agricultural productivity; (2) in areas identified as grain production hotspots, there were stronger positive correlations between grain output and carbon sequestration services, soil conservation, and water yields than the regional averages, suggesting more pronounced mutual benefits; (3) the implementation of strategic initiatives such as controlling soil erosion, expanding afforestation efforts, and enhancing water-saving irrigation infrastructure could simultaneously boost ecological services and agricultural productivity. These results significantly enhance our comprehension of the interplay between ecosystem services in the Hexi Corridor and present practical approaches for the optimization of regional agricultural systems. Full article

The growing mismatch between ecosystem service (ES) supply and demand underscores the importance of thoroughly understanding their spatiotemporal patterns and key drivers to promote ecological civilization and sustainable development at the regional level in China. This study investigates six key ES indicators across mainland China—habitat quality (HQ), carbon sequestration (CS), water yield (WY), sediment delivery ratio (SDR), food production (FP), and nutrient delivery ratio (NDR)—by integrating a suite of analytical approaches. These include a spatiotemporal analysis of trade-offs and synergies in supply, demand, and their ratios; self-organizing maps (SOM) for bundle identification; and interpretable machine learning models. While prior research studies have typically examined ES at a single spatial scale, focusing on supply-side bundles or associated drivers, they have often overlooked demand dynamics and cross-scale interactions. In contrast, this study integrates SOM and SHAP-based machine learning into a dual-scale framework (grid and city levels), enabling more precise identification of scale-dependent drivers and a deeper understanding of the complex interrelationships between ES supply, demand, and their spatial mismatches. The results reveal pronounced spatiotemporal heterogeneity in ES supply and demand at both grid and city scales. Overall, the supply services display a spatial pattern of higher values in the east and south, and lower values in the west and north. High-value areas for multiple demand services are concentrated in the densely populated eastern regions. The grid scale better captures spatial clustering, enhancing the detection of trade-offs and synergies. For instance, the correlation between HQ and NDR supply increased from 0.62 (grid scale) to 0.92 (city scale), while the correlation between HQ and SDR demand decreased from −0.03 to −0.58, indicating that upscaling may highlight broader synergistic or conflicting trends missed at finer resolutions. In the spatiotemporal interaction network of supply–demand ratios, CS, WY, FP, and NDR persistently show low values (below −0.5) in western and northern regions, indicating ongoing mismatches and uneven development. Driver analysis demonstrates scale-dependent effects: at the grid scale, HQ and FP are predominantly influenced by socioeconomic factors, SDR and WY by ecological variables, and CS and NDR by climatic conditions. At the city level, socioeconomic drivers dominate most services. Based on these findings, nine distinct supply–demand bundles were identified at both scales. The largest bundle at the grid scale (B3) occupies 29.1% of the study area, while the largest city-scale bundle (B8) covers 26.5%. This study deepens the understanding of trade-offs, synergies, and driving mechanisms of ecosystem services across multiple spatial scales; reveals scale-sensitive patterns of spatial mismatch; and provides scientific support for tiered ecological compensation, integrated regional planning, and sustainable development strategies. Full article

How can we more fully analyze potential progress toward the 17 Sustainable Development Goals, globally and by country? Methodological challenges include (1) the comprehensiveness of issue coverage, integration of causal elaboration, and geographic detail in available models; (2) clear quantification of goal targets; and (3) specification of scenario interventions that connect meaningfully to the potential leverage of agents. This study uses a large-scale, global but country-based analytical system that tightly integrates multiple issue-area models to push against methodological challenges. It explores the prospects for progress toward selected quantified targets across all goals, using scenarios that consider potential agency-linked interventions relative to the Current Path (CP). The scenarios distinguish interventions focused on Human Development (HD) and natural system sustainability (NSS) plus a Combined SDG scenario (CSDG). Even with a large, integrated push through 2030 and 2050, the world in aggregate will fail to reach many targets, and a great many of the 188 countries represented will fall short. Also of interest is possible tension between the underlying thrusts of HD- and NSS-oriented interventions. Both the Current Path of key variables and intervention leverage constraints make NSS goals harder to reach than HD goals. Because synergies of action considerably outweigh trade-offs, however, complementarity better characterizes the two intervention sets. Full article

Agrivoltaic (Agri-PV) systems face the critical challenge of balancing photovoltaic energy generation with crop productivity, yet systematic approaches to quantifying the trade-offs between these objectives remain scarce. In this study, we identify nine essential design indicators: panel tilt angle, elevation, photovoltaic coverage ratio, shading factor, land equivalent ratio, photosynthetically active radiation (PAR) utilization, crop yield stability index, water use efficiency, and return on investment. We introduce a novel dual matrix Analytic Hierarchy Process (AHP) to evaluate their relative significance. An international panel of eighteen Agri-PV experts, encompassing academia, industry, and policy, provided pairwise comparisons of these indicators under two objectives: maximizing annual energy yield and sustaining crop output. The high consistency observed in expert responses allowed for the derivation of normalized weight vectors, which form the basis of two Weighted Influence Matrices. Analysis of Total Weighted Influence scores from these matrices reveal distinct priority sets: panel tilt, coverage ratio, and elevation are most influential for energy optimization, while PAR utilization, yield stability, and elevation are prioritized for crop productivity. This methodology translates qualitative expert knowledge into quantitative, actionable guidance, clearly delineating both synergies, such as the mutual benefit of increased elevation for energy and crop outcomes, and trade-offs, exemplified by the negative impact of high photovoltaic coverage on crop yield despite gains in energy output. By offering a transparent, expert-driven decision-support tool, this framework enables practitioners to customize Agri-PV system configurations according to local climatic, agronomic, and economic contexts. Ultimately, this approach advances the optimization of the food energy nexus and supports integrated sustainability outcomes in Agri-PV deployment. Full article

The wheat curl mite (WCM, Aceria tosichella Keifer), a complex of eriophyid mite species, transmits wheat streak mosaic virus (WSMV) and Triticum mosaic virus (TriMV), which in single or mixed infections cause wheat streak mosaic (WSM) disease—a major threat to wheat production across the U.S. Great Plains. Resistant wheat cultivars bearing Cmc3 and Cmc4 (targeting WCM), Wsm1 and Wsm2 (targeting WSMV), and Wsm1 (targeting TriMV) are widely used to manage this pest–pathogen complex. However, comprehensive studies investigating how these resistance mechanisms influence both vector biology and virus transmission remain scarce. To address this gap, we evaluated disease development and WCM fitness across nine wheat cultivars with differential resistance profiles under single and mixed infections of WSMV and TriMV. We found strong viral synergy in co-infected plants, with TriMV accumulation markedly enhanced during mixed infections, irrespective of host genotype. Symptom severity and virus titers (both WSMV and TriMV) were highest in the cultivars carrying Wsm2, suggesting a potential trade-off in resistance effectiveness under mixed infection pressure. While mite development time (egg to adult) was unaffected by host genotype or infection status, mite fecundity was significantly reduced on infected plants carrying Wsm1 or Wsm2, but not on those with Cmc3 and Cmc4. Notably, virus accumulation in mites was reduced on the cultivars with Cmc3 and Cmc4, correlating with virus titers in the host tissues. Our findings highlight the complex interplay between host resistance, virus dynamics, and vector performance. Cultivars harboring Cmc3 and Cmc4 may offer robust field-level protection by simultaneously suppressing mite reproduction and limiting virus accumulation in both plant and vector. Full article

As a typical reforested region of the Loess Plateau, the Caijiachuan watershed plays a vital role in ecological security and resource management. This study evaluates the spatiotemporal variations in key ecosystem services—namely soil retention, water yield, carbon storage, and habitat quality—between 2002 and 2024 using the InVEST model, calibrated with field-measured rainfall, carbon density, and high-resolution land use data derived from integrated remote sensing and field surveys. Statistical analyses based on the R language reveal dynamic trade-offs and synergies among these services. The results show that: (1) soil retention, carbon storage, and habitat quality have steadily improved, while water yield shows an overall upward trend with significant spatial heterogeneity; (2) a consistent and significant trade-off exists between carbon storage and water yield (average R² ≈ 0.28), while other ecosystem service interactions are relatively weak; (3) climatic variability, topographic heterogeneity (e.g., slope and elevation), and vegetation structure are key drivers of these trade-offs. This study provides scientific evidence to support ecological management and policy formulation in reforested areas of the Loess Plateau. Full article

This study investigated the effects of macronutrient type and concentration on the biomass yield and biochemical composition of hydroponically grown wheat sprouts (HWS), with the aim of identifying fertilization strategies that optimize both productivity and feed quality. HWS were cultivated using a nutrient film technique over a 7-day period under controlled environmental conditions, with treatments including calcium nitrate (CN1–CN3), potassium phosphate (CP1–CP3), potassium sulfate (CK1–CK2), and a balanced NPK 20–20–20 fertilizer (NPK1–NPK3), each applied at three increasing concentrations. The quantitative parameters assessed included biomass yield per unit of dry seed (DP, kg kg⁻¹) and dry matter content (DM, %), while qualitative traits included crude protein (CP), ether extract (EE), crude fiber (CF), and ash content. Results indicated that balanced NPK fertilization significantly enhanced performance, with NPK3 achieving the highest biomass yield (6.39 kg kg⁻¹), CP (24.26%), CF (5.63%), and ash (16.0%) content. In contrast, CN3 treatments reduced yield (4.84 kg kg⁻¹) despite increasing CP (19.65%), indicating trade-offs between nitrogen enrichment and vegetative expansion. Phosphorus-based treatments (CP2–CP3) improved nutrient density without suppressing yield. Regression analyses revealed strong correlations between DM and both CF (R² = 0.81) and ash (R² = 0.71), supporting their utility as indirect indicators of feed quality. EE content remained stable (2.07–2.67%) across all treatments, suggesting its limited responsiveness to macronutrient manipulation. These findings highlight the importance of nutrient synergy in hydroponic systems and provide a practical framework for tailoring fertilization regimes to meet specific agronomic and nutritional objectives in precision livestock feeding and provide practical guidance for optimizing hydroponic livestock feed production. Full article

As China’s economy grows and travel demand increases, its aviation market has evolved to become the second-largest in the world. This study presents a pioneering analysis of China’s aviation network evolution (1990–2024) by integrating temporal dynamics into a network density matrix theory, addressing critical gaps in prior static network analyses. Unlike conventional studies focusing on isolated topological metrics, we introduce a triangulated methodology: ① a network sequence analysis capturing structural shifts in degree distribution, clustering coefficient, and path length; ② novel redundancy–entropy coupling quantifying complexity evolution beyond traditional efficiency metrics; and ③ economic-network coordination modeling with spatial autocorrelation validation. Key innovations reveal previously unrecognized dynamics: ① Time-embedded density matrices ($\rho$) demonstrate how sparsity balances information propagation efficiency ($\eta$) and response diversity, resolving the paradox of functional yet sparse connectivity. ② Redundancy–entropy synergy exposes adaptive trade-offs. Entropy ($H$) rises 18% (2000–2024), while redundancy ($R$) rebounds post-2010 (0.25→0.33), reflecting the strategic resilience enhancement after early efficiency-focused phases. ③ Economic-network coupling exhibits strong spatial autocorrelation ($Moran’sI>0.16$, $p<0.05$), with eastern China achieving “primary coordination”, while western regions lag due to geographical constraints. The empirical results confirm structural self-organization. Power-law strengthening, route growth exponentially outpacing cities, and clustering ($C$) rising 16% as the path length ($L$) increases, validating the hierarchical hub formation. These findings establish aviation networks as dynamically optimized systems where economic policies and topological laws interactively drive evolution, offering a paradigm shift from descriptive to predictive network management. Full article

Understanding the relationship between regional vegetation dynamics and water resources is essential for improving integrated vegetation–water management, enhancing ecosystem services, and advancing the sustainable development of ecological–economic–social systems. As China’s second largest river basin, the Yellow River Basin (YRB) is ecologically fragile and experiences severe water scarcity. Vegetation changes further intensify conflicts between water supply and demand. To investigate the evolution and interaction mechanisms between vegetation and water resources in the YRB, this study uses the InVEST model to simulate annual water yield (Wyield) from 1982 to 2020 and applies the Dimidiate Pixel Model (DPM) to estimate fractional vegetation cover (FVC). The Theil–Sen method is applied to quantify the spatiotemporal trends of Wyield and FVC. A pixel-based second-order partial correlation analysis is performed to clarify the intrinsic relationship between FVC and Wyield at the grid scale. The main conclusions are as follows: (1) During the statistical period (1982–2020), the multi-year average annual Wyield in the YRB was 73.15 mm. Interannual Wyield showed a clear fluctuating trend, with an initial decline followed by a subsequent increase. Wyield showed marked spatial heterogeneity, with high values in the southern upper reaches and low values in the Longzhong Loess Plateau and Hetao Plain. During the same period, about 68.74% of the basin experienced increasing Wyield, while declines were concentrated in the upper reaches. (2) The average FVC across the basin was 0.51, showing a significant increasing trend during the statistical period. The long-term average FVC showed significant spatial heterogeneity, with high values in the Fenwei Plain, Shanxi Basin, and Taihang Mountains, and low values in the Loess Plateau and Hetao Plain. Spatially, 68.74% of the basin exhibited significant increases in FVC, mainly in the middle and lower reaches, while decreases were mostly in the upper reaches. (3) Areas with significant FVC–Wyield correlations covered a small portion of the basin: trade-off regions made up 10.35% (mainly in the southern upper reaches), and synergistic areas accounted for 5.26% (mostly in the Hetao Plain and central Loess Plateau), both dominated by grasslands and croplands. Mechanistic analysis revealed spatiotemporal heterogeneity in FVC–Wyield relationships across the basin, influenced by both natural drivers and anthropogenic activities. This study systematically explores the patterns and interaction mechanisms of FVC and Wyield in the YRB, offering a theoretical basis for regional water management, ecological protection, and sustainable development. Full article

[Objective] To quantify key ecosystem services within the Dongting Lake region, clarify the trade-off/synergy relationships, and detect the driving factors in order to support the ecological sustainable development of the Dongting Lake region. [Methods] Using the InVEST model, taking the area around Dongting Lake as the study area, four ecosystem services including water yield, carbon storage, soil conservation, and habitat quality were quantitatively assessed. Interdependencies between ecosystem services were assessed using correlation analysis to quantify trade-offs/synergies, and the geodetector model was used to detect their driving factors. [Results] (1) From 2000 to 2020, the soil retention service and water yield service in the Dongting Lake area showed an increasing trend over time. The total water yield increased from 4.93 × 10¹⁰ m³ to 6.71 × 10¹⁰ m³, while the total soil retention increased from 4.46 × 10⁹ t to 5.77 × 10⁹ t; habitat quality and total carbon storage continued to decline, with habitat quality decreasing from 0.6906 to 0.6785 and carbon storage decreasing from 1.480 × 10⁹ t to 1.476 × 10⁹ t. (2) In the study area, significant synergistic effects existed between carbon storage and habitat quality, carbon storage and soil retention, carbon storage and water yield, habitat quality and soil retention, and soil retention and water yield. However, there was a significant trade-off relationship between habitat quality and water yield. (3) During the study period, ecosystem service trade-offs and synergy relationships in the Dongting Lake area were jointly influenced by natural factors and human activities. Ranked by the magnitude of driving factor influence, they were land use type, land use intensity, vegetation coverage, temperature, and nighttime light. [Conclusions] Synergies dominated the ecosystem services in the research region, and the influence of natural factors behind them was greater than that of human activities. These research conclusions offer a scientific foundation for the institutional construction of the ecological compensation mechanism in the Dongting Lake basin. Full article

As a fundamental technology in environmental perception, sound source localization (SSL) plays a critical role in public safety, marine exploration, and smart home systems. However, traditional methods such as beamforming and time-delay estimation rely on manually designed physical models and idealized assumptions, which struggle to meet practical demands in dynamic and complex scenarios. Recent advancements in deep learning have revolutionized SSL by leveraging its end-to-end feature adaptability, cross-scenario generalization capabilities, and data-driven modeling, significantly enhancing localization robustness and accuracy in challenging environments. This review systematically examines the progress of deep learning-based SSL across three critical domains: marine environments, indoor reverberant spaces, and unmanned aerial vehicle (UAV) monitoring. In marine scenarios, complex-valued convolutional networks combined with adversarial transfer learning mitigate environmental mismatch and multipath interference through phase information fusion and domain adaptation strategies. For indoor high-reverberation conditions, attention mechanisms and multimodal fusion architectures achieve precise localization under low signal-to-noise ratios by adaptively weighting critical acoustic features. In UAV surveillance, lightweight models integrated with spatiotemporal Transformers address dynamic modeling of non-stationary noise spectra and edge computing efficiency constraints. Despite these advancements, current approaches face three core challenges: the insufficient integration of physical principles, prohibitive data annotation costs, and the trade-off between real-time performance and accuracy. Future research should prioritize physics-informed modeling to embed acoustic propagation mechanisms, unsupervised domain adaptation to reduce reliance on labeled data, and sensor-algorithm co-design to optimize hardware-software synergy. These directions aim to propel SSL toward intelligent systems characterized by high precision, strong robustness, and low power consumption. This work provides both theoretical foundations and technical references for algorithm selection and practical implementation in complex real-world scenarios. Full article

This study introduces a rigid–flexible coupled constant force actuator integrated with Active Disturbance Rejection Control (ADRC) to tackle the rigidity–compliance trade-off in precision force-sensitive applications. The actuator utilizes compliant hinges to decrease contact stiffness by three orders of magnitude (${10}^6\to {10}^3 \mathrm{N}/\mathrm{m}$), facilitating effective force management through millimeter-scale placement (0.1∼1 mm) and inherently mitigating high-frequency disturbances. The ADRC framework, augmented by an Extended State Observer (ESO), dynamically assesses and compensates for internal nonlinearities (such as friction hysteresis) and external disturbances without necessitating accurate system models. Experimental results indicate enhanced performance compared to PID control: under dynamic disturbances, force deviations are limited to $\pm 0.2 \mathrm{N}$ with a 98.5% reduction in mean absolute error, a 96.3% increase in settling speed, and 99% suppression of oscillations. The co-design of mechanical compliance with model-free control addresses the constraints of traditional high-stiffness systems, providing a scalable solution for industrial robots, compliant material processing, and medical device operations. Validation of the prototype under sinusoidal perturbations demonstrates reliable force regulation (settling time $<0.56 \mathrm{s}$, errors $<0.5 \mathrm{N}$), underscoring its relevance in dynamic situations. This study integrates theoretical innovation with experimental precision, enhancing intelligent manufacturing systems via adaptive control and structural synergy. Full article