Search Results (1,309)

The exploration of the ecosystem service value of rural tourism destinations and their driving factors is regarded as an important approach for promoting the high-quality development of rural tourism and achieving rural revitalization. At present, both industry and academia lack quantitative analyses and integrated optimization approaches for small-scale landscape elements within the context of rural tourism destinations. An examination of rural ecosystem service values from a small-scale perspective can assist rural areas in precisely enhancing ecological functions, advancing rural landscape construction, and fostering high-quality rural development. Six sample sites within rural tourism areas in the Yangtze River Delta region were selected, and the functional value method, willingness-to-pay method, and binary logistic regression model were comprehensively applied to assess ecosystem service values and their influencing factors. The results indicate that: (1) Significant differences exist in ecosystem service values across small-scale rural landscapes, primarily attributable to variations in cultural service values, which constitute the dominant component of the overall value. (2) Cultural service values are manifested in tourists’ willingness to pay, which is closely associated with the configuration types of rural small-scale landscapes. (3) Tourists’ willingness to pay is primarily influenced by their cognition of cultural services and by psychological perception factors. According to the regression results, perceived importance of cultural service protection, concerns regarding damage, levels of tourist satisfaction, and willingness to revisit exert significant negative effects on willingness to pay. (4) High-demand tourism motives exhibit only a weak correlation with willingness to pay. (5) Low-demand motivations significantly suppress willingness to pay. The conclusions serve as a reference for the quantification of small-scale rural landscape values and the examination of mechanisms underlying their multiple influencing factors, as well as for the optimization of rural landscape planning, design, and sustainable management practices. Full article

This study applies the Contingent Valuation Method (CVM) to estimate the non-use value of Laojun Mountain National Park, a culturally and ecologically significant site within the Three Parallel Rivers World Heritage region of northwestern Yunnan, China. Based on 219 valid survey responses, the analysis identifies education, income, occupation, cultural identity, and recognition of legacy values as significant determinants of willingness to pay (WTP) for conservation. Interaction effect logistic regression shows that the influence of cultural identity on WTP is moderated by income level and ecological awareness. Valuation results indicate that the park’s annual non-use value ranges from 79.697 to 260.841 billion yuan, based on median and mean estimates. Motivational analysis highlights aesthetic appreciation, cultural meaning, and intergenerational ethics as key drivers of conservation support, while refusal to pay is primarily attributed to expectations of governmental responsibility, especially among low-income and less-educated respondents. These findings advance theoretical understanding of bio-cultural valuation, offer practical guidance for the design of Payment for Ecosystem Services (PES) schemes, and underscore the importance of integrating socio-cultural dimensions into sustainable conservation finance and policy strategies. Full article

Yellow River Delta National Nature Reserve plays a critical role in ecological conservation, and assessing its ecosystem service value (ESV) is essential for guiding sustainable management strategies that harmonize development and preservation. This study was motivated by the need to generate actionable insights for adaptive conservation planning in this vulnerable coastal region. We evaluated the spatiotemporal dynamics of ESV from 2000 to 2020 using a combination of remote sensing, geographic information system analyses, and statistical modeling. Primary drivers influencing the spatial heterogeneity of ecosystem service value were identified through geographical detector analysis, and future trends were projected based on historical patterns. The results revealed that (1) ESV showed a clear spatial gradient, with higher values in coastal zones, moderate values along river channels, and lower values inland, and exhibited an overall significant increase over the two decades, primarily driven by improvements in regulating services; (2) wetland area and precipitation were the most influential factors, though socio-economic elements and environmental conditions also contributed to ESV distribution; and (3) future ESV is expected to follow current trends, reinforcing the importance of current management practices. Given that the continuous increase in ESV from 2000 to 2020 was predominantly attributed to water body expansion, future conservation strategies should prioritize the protection and restoration of these water resources. Full article

This study provides the first comprehensive, field-inventory-based assessment of urban ecosystem services within a Russian university campus, focusing on the woody vegetation of the Lobachevsky State University of Nizhny Novgorod. Utilizing a detailed field tree inventory combined with the i-Tree framework (including i-Tree Eco, i-Tree Canopy, UFORE, and i-Tree Hydro models), we quantified the campus’s capacity for carbon storage and sequestration, air pollutant removal, and stormwater runoff mitigation. The campus green infrastructure, comprising 1887 trees across 32 species with a density of 145.5 stems per hectare, demonstrated significant ecological value. Results show a carbon storage density of 26.61 t C ha⁻¹ and an annual gross carbon sequestration of 11.43 tons. Furthermore, the campus trees removed 1213.7 kg of air pollutants annually (a deposition rate of 9.35 g m⁻²), with ozone, particulate matter, and sulfur dioxide showing the highest deposition. The campus also retained 956.1 m³ of stormwater annually. These findings, particularly the high carbon sequestration rates, are attributed to the dominance of relatively young, fast-growing tree species. This research establishes a critical baseline for understanding urban ecosystem services in a previously under-researched geographical context. The detailed, empirical data offers crucial insights for urban planners and policymakers in Nizhny Novgorod and beyond, advocating for the strategic integration of ecosystem services assessments into campus planning and broader urban green infrastructure development across Russian cities. The study underscores the significant role of university campuses as vital components of urban green infrastructure, contributing substantially to environmental sustainability and human well-being. Full article

Forest fire regimes are undergoing systematic reorganization under climate change, particularly in monsoon–human coupled ecosystems such as Southeastern China, where risk dynamics remain poorly quantified. This study proposes a meteorology-driven machine learning model designed to assess long-term forest fire risk. Using kernel density estimation and standard deviational ellipse analysis, we assessed the spatiotemporal patterns of fire risk during the observational period and their future shifts across the SSP1-2.6 and SSP5-8.5 scenarios. The results indicate a significant overall decline in fire frequency from 2008 to 2024 (−467.3 fires/year, representing an annual average reduction of 10.8%, p < 0.001), which is attributed primarily to enhanced regional fire prevention and control measures, yet with a notable reversal after 2016 in Guangdong and Fujian. Fires are highly seasonal, with 74% occurring in the dry season (December–March). The meteorologically driven random forest model exhibited excellent performance (R² = 0.889), validating meteorological conditions as key drivers of regional fire dynamics. It is projected that intensified warming (+5.5 °C under SSP5-8.5) and increased precipitation variability (+23%) are likely to drive pronounced northward and inland migration in high-risk zones. Our projections indicate that by the end of the century, high-risk area coverage could expand to 19.2%, with a shift from diffuse to clustered patterns, particularly in Jiangsu and Zhejiang. These findings underscore the critical role of hydrothermal reconfiguration in reshaping fire risk geography and highlight the need for dynamic, region-specific fire management strategies in response to compound climate risks. Full article

Energy consumption and environmental pollution pose significant challenges to sustainable development. This study develops a comprehensive coupled framework model that advances the quantitative integration of carbon (C), nitrogen (N), and phosphorus (P) cycles driven by multiple anthropogenic pollution sources. This paper used Panjin city as a case study to analyze the dynamic changes and interconnections among C, N, and P. Results indicated that net anthropogenic carbon inputs (NAI_C) increased by 33% from 2016–2020, while net anthropogenic nitrogen inputs (NAI_N) and net anthropogenic phosphorus inputs (NAI_P) decreased by 14% and 28%, respectively. The primary driver of NAI_C was energy consumption, while wetlands were the dominant carbon sequestration sink. Agricultural production was identified as the primary source of NAI_N and NAI_P, and approximately 4.5% of NAI_N and 2.9% of NAI_P were discharged into receiving water bodies. We demonstrate that human activities and natural processes exhibit dual attributes, producing positive and negative environmental effects. The increase in carbon emissions drives economic growth and industrial restructuring; however, the enhanced economic capacity also strengthens the ability to mitigate pollution through environmental protection measures. Similarly, natural ecosystems, including forests and grasslands, contribute to carbon sequestration and the release of non-point source pollution. The comprehensive environmental impact assessment of C, N, and P revealed that the comprehensive environmental index for Panjin city exhibited an improved trend. The factors of energy structure, energy efficiency, and economic scale promoted NAI_C growth, with the economic scale factor alone accounting for 93% of the total increment. Environmental efficiency factor and population size factor were the primary drivers in reducing NAI_N and NAI_P discharges into the receiving water bodies. We propose a novel management model, ecological restoration, clean energy utilization, resource recycling, and pollution source reduction to achieve systemic governance of C, N, and P inputs. Full article

The Yellow River Delta is one of China’s most ecologically fragile regions, experiencing prolonged pressures from rapid urbanization and ecological degradation. Existing research, however, has predominantly focused on constructing ecological security patterns under single scenarios, with limited systematic multi-scenario comparisons and insufficient statistical support. To address this gap, this study proposes an integrated framework of “land use simulation—multi-scenario ecological security pattern construction—statistical comparative analysis.” Using the PLUS model, three scenarios were constructed—Business-as-Usual (BAU), Priority Urban Development (PUD), and Priority Ecological Protection (PEP)—to simulate land use changes by 2040. Habitat quality assessment, Multi-Scale Pattern Analysis (MSPA), landscape connectivity, and circuit theory were integrated to identify ecological source areas, corridors, and nodes, incorporating a novel hexagonal grid partitioning method. Statistical significance was evaluated using parametric tests (ANOVA, t-test) and non-parametric tests (permutation test, PERMANOVA). Analysis indicated significant differences in ecological security patterns across scenarios. Under the PEP scenario, ecological source areas reached 3580.42 km² (12.39% of the total Yellow River Delta), corresponding to a 14.85% increase relative to the BAU scenario and a 32.79% increase relative to the PUD scenario. These gains are primarily attributable to stringent wetland and forestland protection policies, which successfully limited the encroachment of construction land into ecological space. Habitat quality and connectivity markedly improved, resulting in the highest ecosystem stability. By contrast, the PUD scenario experienced an 851.46 km² expansion of construction land, resulting in the shrinkage of ecological source areas and intensified fragmentation, consequently increasing ecological security risks. The BAU scenario demonstrated moderate outcomes, with a moderately balanced spatial configuration. In conclusion, this study introduces an ecological restoration strategy of “five zones, one belt, one center, and multiple corridors” based on multi-scenario ecological security patterns. This provides a scientific foundation for ecological restoration and territorial spatial planning in the Yellow River Delta, while the proposed multi-scenario statistical comparison method provides a replicable methodological framework for ecological security pattern research in other delta regions. Full article

National-scale long-term forest ecosystem surveys based on systematic sampling offer a robust framework for detecting temporal growth trends of specific tree species across regions. The National Forest Inventory (NFI) of the Republic of Korea serves as a vital source for analyzing long-term forest dynamics on a national scale by providing regularly collected large-scale forest data. However, various limitations, such as the lack of individual-level and spatial interaction data, restrict the development of reliable individual tree growth models. To overcome this, distance-independent models, compatible with the structure and data resolution of the NFI, provide a practical alternative for simulating individual tree and stand-level growth by utilizing straightforward attributes, such as diameter at breast height (DBH). This study aimed to analyze the growth patterns and construct species-specific models for two major plantation species in South Korea, Pinus koraiensis and Larix kaempferi, using data from the 5th (2006–2010), 6th (2011–2015), and 7th (2016–2020) NFI survey cycles. The sampling points included 117 and 171 plots for P. koraiensis and L. kaempferi, respectively. An additional matching process was implemented to improve species identification and tracking across multiple survey years. The final models were parameterized using a distance-independent model, integrating the estimation of potential diameter growth (PG) and a modifier (MOD) function to adjust for species- and site-specific variabilities. Consequently, the models for each species demonstrated strong performance, with P. koraiensis showing an R² of 0.98 and RMSE of 1.15 (cm), and L. kaempferi showing an R² of 0.98 and RMSE of 1.14 (cm). This study provides empirical evidence for the development of generalized and scalable growth models using NFI data. As the NFI increases in volume, the framework can be expanded to underrepresented species to improve the accuracy of underperforming models. Ultimately, this study lays a scientific foundation for the future development of tree-level simulation algorithms for forest dynamics, encompassing mortality, harvesting, and regeneration. Full article

Coal mining disturbances in semi-arid grasslands affect land surface phenology (LSP), impacting ecosystem functions, restoration target setting, and carbon sequestration; however, the magnitude and spatial extent of these disturbances and their detectability across vegetation indices (VIs), remain insufficiently constrained. We developed and applied a streamlined quantitative framework to delineate the extent and intensity of mining-induced phenological disturbance and to compare the sensitivity and stability of commonly used VIs. Using Harmonized Landsat Sentinel (HLS) surface reflectance data over the Yimin mine, we reconstructed multitemporal VI trajectories and derived phenological metrics; directional phenology gradients were used to delineate disturbance, and VI responsiveness was evaluated via mean difference (MD) and standard deviation (SD) between affected and control areas. Research findings indicate that the impact of mining extends to an area approximately four times the size of the mining site, with the start of season (SOS) in affected areas occurring about 10 days later than in unaffected areas. Responses varied markedly among VIs, with the Modified Soil-Adjusted Vegetation Index (MSAVI) exhibiting the highest spectral stability under disturbance. This framework yields an information-rich quantification of phenological impacts attributable to mining and provides operational guidance for index selection and the prioritization of restoration and environmental management in semi-arid mining landscapes. Full article

(1) Background: Marine eutrophication represents a formidable challenge to sustainable global aquaculture, posing a severe threat to marine ecosystems and impeding the achievement of UN Sustainable Development Goal 14. Current methodologies for identifying eutrophication events and tracing their drivers from vast, heterogeneous text data rely on manual analysis and thus have significant limitations. (2) Methods: To address this issue, we developed a novel automated attribution analysis framework. We first pre-trained a domain-specific model (Aquaculture-BERT) on a 210-million-word corpus, which is the foundation for constructing a comprehensive Aquaculture Eutrophication Knowledge Graph (AEKG) with 3.2 million entities and 8.5 million relations. (3) Results: Aquaculture-BERT achieved an F1-score of 92.1% in key information extraction, significantly outperforming generic models. The framework successfully analyzed complex cases, such as Xiamen harmful algal bloom, generating association reports congruent with established scientific conclusions and elucidating latent pollution pathways (e.g., pond aquaculture–nitrogen input–Phaeocystis bloom). (4) Conclusions: This study delivers an AI-driven framework that enables the intelligent and efficient analysis of aquaculture-induced eutrophication, propelling a paradigm shift toward the deep integration of data-driven discovery with hypothesis-driven inquiry. The framework provides a robust tool for quantifying the environmental impacts of aquaculture and identifying pollution sources, contributing to sustainable management and achieving SDG 14 targets. Full article

Today, the abundance of personal care product (PCP) ingredients and UV filters (UVFs) in coastal marine environments is a growing concern worldwide. In addition, mussels are the most commonly used sentinel organisms in bio-monitoring programs. In the current study, we collected mussels (Mytilus galloprovincialis) (over 6 months) from three seawater sites in Tunisia (Monastir, Sousse, and Mahdia). Analysis of the samples by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) revealed the presence of 13 compounds among the 18 PCP ingredients and UVFs investigated. Avobenzone (AVO) and tert-butyl hydroxyphenyl benzotriazole (TBHPBT) were the most frequently observed, ranging from 121.076 ± 1.6 to 193.481 ± 5.5 ng g⁻¹ and 20.987 ± 0.7 to 26.704 ± 1.7 ng g⁻¹, respectively, with maximum values in the city of Sousse. 4-Hydroxybenzophenone (4HB) and benzophenone-1 (BP1) were also found in all mussel samples with levels in the range of 26.745 ± 0.4 ng g⁻¹ and 12.53 ± 0.5 ng g⁻¹, respectively. We observed a positive correlation with the chemical characterization of the contaminated seawater. The environmental hazards of PCP ingredients were estimated with the aim of performing a preliminary risk assessment at the environmental level. For this purpose, the estimated daily intake (EDI) of a substance was calculated. The results obtained revealed a high value of up to 68.36 ng kg body-weight⁻¹ day⁻¹. The high concentration observed in the samples reported for the target PCP ingredients could be partly attributed to their inefficient removal before being released into the sea. We now know that PCP ingredients and UVFs cause irreparable damage to coastal ecosystems and pose the greatest risk to the aquatic organisms tested. Full article

Terrestrial cross-boundary inputs of leaf litter serve as a critical foundation for secondary productivity in freshwater ecosystems. The regulatory mechanisms of tannins in leaf litter on degradation rates under submerged conditions remain unclear. This study employed leaf litter from low-tannin plants Osmanthus fragrans (A) and Canna glauca (B) as decomposition substrates, with the high-tannin species Myriophyllum verticillatum (C) incorporated to adjust tannin levels. A 140-day hydroponic degradation experiment was conducted under controlled temperature and dark conditions, which included four mixed litter treatments with a gradient of tannin additions (AB as the control, 0 g; ABC1: 0.5 g; ABC2: 2.5 g; ABC3: 4.5 g) along with two single-species treatments (A and B). The following results were found: (1) Low tannin levels (ABC1) promoted degradation rates of A and B (increased by 1.33–12.70%), whereas high tannin (ABC3) inhibited decomposition (decreased by 6.21–6.82%). (2) Tannin–protein complexes reduce nitrogen bioavailability and inhibit nitrification, thereby disrupting the nitrogen cycle in aquatic systems. In ABC3, total nitrogen content in A and B litter increased by 17.69–26.46% compared to AB, with concurrent 59.29% elevation in water NH₄⁺-N concentration. (3) High tannin induced dominance of oligotrophic stress-resistant bacterial communities (e.g., Treponema) through nutrient limitation and toxicity stress; however, their low metabolic efficiency reduced overall decomposition efficiency. Research reveals that the ecological benefits of plant secondary metabolites outweigh their nutritional quality attributes. Full article

Marine mammals are important ecological bio-indicators of marine ecosystems impacted by a plethora of anthropogenic and environmental threats. Genomics detects genetic variation, adaptation to environmental shifts, and susceptibility to diseases in marine mammal species. In this study, eDNA was utilized for the first time in the Pagasitikos Gulf over three consecutive years (2022–2024) in order to detect marine mammal species. Additionally, visual monitoring and eDNA results were compared to reveal the pros and cons of the two methodologies. The gulf was zoned into five different areas with respect to oceanographic features for sampling. DNA extraction was assessed by using a standard protocol of phenol–chloroform followed by PCR amplification using the 16S rRNA gene. A total of 5,209,613 highly filtered sequence reads were attributed to 108 species. Among these, Monachus monachus, Tursiops truncatus, and Ziphius cavirostris species were detected. This novel detection of Z. cavirostris in the relatively shallow waters of the Gulf of Pagasitikos raised the question of whether it was a random event or a new ecological trend. Z. cavirostris and M. monachus appeared to share the same marine areas within the gulf. In the era of the climate crisis, eDNA provides essential information on marine mammals’ ecological status, yields novel detections, and predicts behavioral changes essential to deep-diving species. Full article

Atmospheric sulfur (S) deposition, a key component of acid deposition, poses risks to ecosystems, human health, and sustainable development. In China, decades of coal-dominated energy use caused severe S pollution, but recent emission-control policies and energy restructuring have sought to reverse this trend. However, the effectiveness and regional differences in these measures remain insufficiently quantified. Here, we combined continuous observations from 43 monitoring sites (2013–2023), satellite-derived SO₂ vertical column density, and multi-source environmental datasets to construct a high-resolution record of wet S deposition. A random forest model, validated with R² = 0.52 and RMSE = 1.2 kg ha⁻¹ yr⁻¹, was used to estimate fluxes and spatial patterns, while ridge regression and SHAP analysis quantified the relative contributions of emissions, precipitation, and socioeconomic factors. This framework allows us to assess both the environmental and health-related sustainability implications of sulfur deposition. Results show a nationwide decline of more than 50% in wet S deposition during 2013–2023, with two-thirds of sites and 95% of grids showing significant decreases. Historical hotspots such as the North China Plain and Sichuan Basin improved markedly, while some southern provinces (e.g., Guizhou, Hunan, Jiangxi) still exhibited high deposition (>20 kg ha⁻¹ yr⁻¹). Over 90% of the reduction was attributable to emission declines, confirming the dominant effect of sustained policy-driven measures. This study extends sulfur deposition records to 2023, demonstrates the value of integrating ground monitoring with remote sensing and machine learning, and provides robust evidence that China’s emission reduction policies have delivered significant environmental and sustainability benefits. The findings offer insights for region-specific governance and for developing countries balancing economic growth with ecological protection. Full article

In the integrated management of water resources, which includes protecting and restoring ecosystems that are directly and indirectly dependent on water, a crucial issue is assessing and identifying areas with the greatest need for improved water retention. This study presents an effective and easy-to-apply method based on the multicriteria decision-making approach, which analyses needs and feasibility. Until now, a point bonitation method has been used to evaluate the need to increase the retention capacity of specific areas. Modification of this method involved applying the Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach to estimate the weights of the analysed criteria. The results obtained using the new method were compared with previous studies assessing retention needs in the Masovian Voivodeship (Poland), which relied on the point bonitation method. The final evaluation showed a 74% compliance rate while significantly reducing expert involvement, demonstrating the high applicability of the developed method. Moreover, the DEMATEL method enabled the development of a cause-and-effect model of the criteria and an analysis of their importance. The lowest level of importance (13.6%) was attributed to climatic conditions, while the significance of the remaining criteria (hydrological and hydrogeological conditions, economic use of the catchment area, and catchment area cover) varied within a narrow range, from 20% to 23.5%. Full article