Search Results (2,519)

In river-connected lake regions, both land use and hydrological regime changes may affect the ecosystem services; however, few studies have attempted to elucidate their complex influences. In this study, the spatiotemporal dynamics of eight ecosystem services (crop production, aquatic production, water yield, soil retention, flood regulation, water purification, net primary productivity, and habitat quality) were investigated through remote-sensing images and the InVEST model in the Dongting Lake Region during 2000–2020. Results revealed that crop and aquatic production increased significantly from 2000 to 2020, particularly in the northwestern and central regions, while soil retention and net primary productivity also improved. However, flood regulation, water purification, and habitat quality decreased, with the fastest decline in habitat quality occurring at the periphery of the Dongting Lake. Land-use types accounted for 63.3%, 53.8%, and 40.3% of spatial heterogeneity in habitat quality, flood regulation, and water purification, respectively. Land-use changes, particularly the expansion of construction land and the conversion of water bodies to cropland, led to a sharp decline in soil retention, flood regulation, water purification, net primary productivity, and habitat quality. In addition, crop production and aquatic production were higher in cultivated land and residential land, while the accompanying degradation of flood regulation, water purification, and habitat quality formed a “production-pollution-degradation” spatial coupling pattern. Furthermore, hydrological fluctuations further complicated these dynamics; wet years amplified agricultural outputs but intensified ecological degradation through spatial spillover effects. These findings underscore the need for integrated land-use and hydrological management strategies that balance human livelihoods with ecosystem resilience. Full article

The ecological impact of crown-of-thorns starfish (CoTS; Acanthaster spp.) on coral reefs is intrinsically linked to their feeding behaviour. Management thresholds designed to mitigate coral loss driven by elevated densities of crown-of-thorns starfish rely on accurate estimates of individual feeding rates. In this study, structure-from-motion photogrammetry and intensive tracking of adult Pacific CoTS over an extended survey period were used to generate three-dimensional, high-resolution estimates of daily feeding rates. Our findings revealed substantial variation in the areal extent of coral consumed, both across consecutive days and among individuals. Notably, CoTS did not feed consistently; feeding occurred on 65% of observation days, with 2–3 days periods of inactivity common. Despite this variability, mean daily feeding rates aligned with previous studies (1.35 coral colonies d⁻¹; 198.4 cm² day⁻¹ planar area, and 998.83 cm² day⁻¹ three-dimensional surface area). Across all tracked individuals (n = 8), feeding was recorded on 17 coral genera; however, Acropora alone accounted for 51% of colonies consumed and contributed 82% of the total three-dimensional surface area ingested during the survey period. This highlights the disproportionately large feeding yield derived from Acropora-dominated diets and raises important questions about how future declines in Acropora cover may impact CoTS feeding success and energetic intake. Full article

The Tibetan-Himalayan region, recognized as a global biodiversity hotspot, is increasingly threatened by the dual pressures of climate change and human activities. Understanding the vulnerability of plant species to these forces is crucial for effective ecological conservation in this region. This study employed an improved Climate Niche Factor Analysis (CNFA) framework to assess the vulnerability of six representative alpine endemic herbaceous plants in this ecologically sensitive region under future climate changes. Our results show distinct spatial vulnerability patterns for the six species, with higher vulnerability in the western regions of the Tibetan-Himalayan region and lower vulnerability in the eastern areas. Particularly under high-emission scenarios (SSP5-8.5), climate change is projected to substantially intensify threats to these plant species, reinforcing the imperative for targeted conservation strategies. Additionally, we found that the current coverage of protected areas (PAs) within the species’ habitats was severely insufficient, with less than 25% coverage overall, and it was even lower (<7%) in highly vulnerable regions. Human activity hotspots, such as the regions around Lhasa and Chengdu, further exacerbate species vulnerability. Notably, some species currently classified as least concern (e.g., Stipa purpurea (S. purpurea)) according to the IUCN Red List exhibit higher vulnerability than species listed as near threatened (e.g., Cyananthus microphyllus (C. microphylla)) under future climate change. These findings suggest that existing biodiversity assessments, such as the IUCN Red List, may not adequately account for future climate risks, highlighting the importance of incorporating climate change projections into conservation planning. Our study calls for expanding and optimizing PAs, improving management, and enhancing climate resilience to mitigate biodiversity loss in the face of climate change and human pressures. Full article

This theoretical essay aims to analyze some of the socio-economic innovations introduced by Platform Capitalism Specifically, it focuses on two main aspects: first, the digital platform as a radical organizational innovation. Digital platforms represent a structural novelty in the market economy, signaling a new organization of production and labor. Second, the essay examines the role of platforms in directly generating value through the concept of “network value”. To this end, it explores the function of “business intelligence” as a strategic and competitive tool. Finally, the paper discusses the key issues associated with platform capitalism, which could threaten its social sustainability and contribute to economic and financial instability. These issues include the increasing commodification of everyday activities, the devaluation of paid labor in favor of free production driven by platform users (the so-called prosumers), and the emergence of proprietary and financial monopolies. Hence, digital platforms do not inherently ensure comprehensive social and environmental sustainability unless supported by targeted economic policy interventions. Conclusively, it is emphasized that defining robust social welfare frameworks—which account for emerging value creation processes—is imperative. Simultaneously, policymakers must incentivize the proliferation of cooperative platforms capable of fostering experimental circular economy models aligned with ecological sustainability. Full article

As an important ecological barrier and animal husbandry resource base in arid and semi-arid areas, grassland degradation directly affects regional ecological security and sustainable development. Ili Prefecture is located in the western part of Xinjiang, China, and is a typical grassland resource-rich area. However, in recent years, driven by climate change and human activities, grassland degradation has become increasingly serious. In view of the lack of comprehensive evaluation indicators and the inconsistency of grassland evaluation grade standards in remote sensing monitoring of grassland resource degradation, this study takes the current situation of grassland degradation in Ili Prefecture in the past 20 years as the research object and constructs a comprehensive evaluation index system covering three criteria layers of vegetation characteristics, environmental characteristics, and utilization characteristics. Net primary productivity (NPP), vegetation coverage, temperature, precipitation, soil erosion modulus, and grazing intensity were selected as multi-source indicators. Combined with data sources such as remote sensing inversion, sample survey, meteorological data, and farmer survey, the factor weight coefficient was determined by analytic hierarchy process. The Grassland Degeneration Comprehensive Index (GDCI) model was constructed to carry out remote sensing monitoring and evaluation of grassland degradation in Yili Prefecture. With reference to the classification threshold of the national standard for grassland degradation, the GDCI grassland degradation evaluation grade threshold (GDCI reduction rate) was determined by the method of weighted average of coefficients: non-degradation (0–10%), mild degradation (10–20%), moderate degradation (20–37.66%) and severe degradation (more than 37.66%). According to the results, between 2000 and 2022, non-degraded grasslands in Ili Prefecture covered an area of 27,200 km², representing 90.19% of the total grassland area. Slight, moderate, and severe degradation accounted for 4.34%, 3.33%, and 2.15%, respectively. Moderately and severely degraded areas are primarily distributed in agro-pastoral transition zones and economically developed urban regions, respectively. The results revealed the spatial and temporal distribution characteristics of grassland degradation in Yili Prefecture and provided data basis and technical support for regional grassland resource management, degradation prevention and control and ecological restoration. Full article

Based on a comprehensive review of the current research status of ecological compensation both domestically and internationally, combined with field survey data, this study delves into the issue of multi-stakeholder participation in the ecological compensation mechanisms of the Xin’an River Basin. This research reveals that the joint participation of multiple stakeholders is crucial to achieving the goals of ecological compensation in river basins. The government plays a significant role in macro-guidance, financial support, policy guarantees, supervision, and management. It promotes the comprehensive implementation of ecological environmental protection by formulating relevant laws and regulations, guiding the public to participate in ecological conservation, and supervising and punishing pollution behaviors. The public, serving as the main force, forms strong awareness and behavioral habits of ecological protection through active participation in environmental protection, monitoring, and feedback. As participants, enterprises contribute to industrial transformation and green development by improving resource utilization efficiency, reducing pollution emissions, promoting green industries, and participating in ecological restoration projects. Scientific research institutions, as technology enablers, have effectively enhanced governance efficiency through technological research and innovation, ecosystem value accounting to provide decision-making support, and public education. Social organizations, as facilitators, have injected vitality and innovation into watershed governance by extensively mobilizing social forces and building multi-party collaboration platforms. Communities, as supporters, have transformed ecological value into economic benefits by developing characteristic industries such as eco-agriculture and eco-tourism. Based on the above findings, further recommendations are proposed to mobilize the enthusiasm of upstream communities and encourage their participation in ecological compensation, promote the market-oriented operation of ecological compensation mechanisms, strengthen cross-regional cooperation to establish joint mechanisms, enhance supervision and evaluation, and establish a sound benefit-sharing mechanism. These recommendations provide theoretical support and practical references for ecological compensation worldwide. Full article

The pepper weevil Anthonomus eugenii is a devastating pest native to Central America that can cause severe damage to over 35 pepper varieties. Global trade in peppers has significantly increased the risk of its spread and expansion. Moreover, future climate change may add more uncertainty to its distribution, resulting in considerable ecological and economic damage globally. Therefore, we employed an ensemble model combining Random Forests and CLIMEX to predict the potential global distribution of A. eugenii in historical and future climate scenarios. The results indicated that the maximum temperature of the warmest month is an important variable affecting global A. eugenii distribution. Under the historical climate scenario, the potential global distribution of A. eugenii is concentrated in the Midwestern and Southern United States, Central America, the La Plata Plain, parts of the Brazilian Plateau, the Mediterranean and Black Sea coasts, sub-Saharan Africa, Northern and Southern China, Southern India, Indochina Peninsula, and coastal area in Eastern Australia. Under future climate scenarios, suitable areas in the Northern Hemisphere, including North America, Europe, and China, are projected to expand toward higher latitudes. In China, the number of highly suitable areas is expected to increase significantly, mainly in the south and north. Contrastingly, suitable areas in Central America, northern South America, the Brazilian Plateau, India, and the Indochina Peninsula will become less suitable. The total land area suitable for A. eugenii under historical and future low- and high-emission climate scenarios accounted for 73.12, 66.82, and 75.97% of the global land area (except for Antarctica), respectively. The high-suitability areas identified by both models decreased by 19.05 and 35.02% under low- and high-emission scenarios, respectively. Building on these findings, we inferred the future expansion trends of A. eugenii globally. Furthermore, we provide early warning of A. eugenii invasion and a scientific basis for its spread and outbreak, facilitating the development of effective quarantine and control measures. Full article

Animal protein production represents a complex system of lives transformed into nutrition, with profound ethical and environmental implications. This study provides a quantitative analysis of animal lives required to produce human-consumable protein across major food production systems. Categorizing animal lives based on cognitive complexity and accounting for all lives involved in production, including direct harvests, reproductive animals, and feed species, reveals dramatic variations in protein efficiency. The analysis considers two categories of animal life: complex-cognitive lives (e.g., mammals, birds, cephalopods) and pain-capable lives (e.g., fish, crustaceans). Calculating protein yield per life demonstrates efficiency differences spanning more than five orders of magnitude, from 2 g per complex-cognitive life for baby octopus to 390,000 g per life for bovine dairy systems. Key findings expose disparities between terrestrial and marine protein production. Terrestrial systems involving mammals and birds show higher protein yields and exclusively involve complex-cognitive lives, while marine systems rely predominantly on pain-capable lives across complex food chains. Dairy production emerges as the most efficient system. Aquaculture systems reveal complex dynamics, with farmed carnivorous fish requiring hundreds of feed fish lives to produce protein, compared to omnivorous species that demonstrate improved efficiency. Beyond quantitative analysis, this research provides a framework for understanding the ethical and ecological dimensions of protein production, offering insights for potential systemic innovations. Full article

Silvopastoral systems, though ecologically beneficial, remain underrepresented in the European Union’s Common Agricultural Policy and are seldom studied in Mediterranean contexts. The current study assesses both the environmental and economic aspects of five typical silvopastoral systems in central Greece, encompassing cattle, sheep, and goat farming. A Life Cycle Assessment approach was implemented to quantify greenhouse gas emissions using economic allocation, distributing impacts between milk and meat outputs. Enteric fermentation was the major emission source, accounting for up to 65.14% of total emissions in beef-based systems, while feeding and soil emissions were more prominent in mixed and small ruminant systems. Total farm-level emissions ranged from 60,609 to 273,579 kg CO₂eq per year. Economically, only beef-integrated systems achieved an average annual profitability above EUR 20,000 per farm, based on financial data averaged over the last five years (2020–2024) from selected case studies in central Greece, while the remaining systems fell below the national poverty threshold for an average household, underscoring concerns about their economic viability. The findings underline the dual challenges of economic viability and policy neglect, stressing the need for targeted support if these multifunctional systems are to add value to EU climate goals and rural sustainability. Full article

The rapid urbanization process has accelerated the degradation of ecosystem services (ESs) in peri-urban rural areas of the Yangtze River Delta (YRD), leading to increasing landscape ecological risks (LERs). Establishing a scientifically grounded landscape ecological risk assessment (LERA) system and corresponding control strategies is therefore imperative. Using rural areas of Jiangning District, Nanjing as a case study, this research proposes an optimized dual-dimensional coupling assessment framework that integrates ecosystem service value (ESV) and ecological risk probability. The spatiotemporal evolution of LER in 2000, 2010, and 2020 and its key driving factors were further studied by using spatial autocorrelation analysis and geodetector methods. The results show the following: (1) From 2000 to 2020, cultivated land remained dominant, but its proportion decreased by 10.87%, while construction land increased by 26.52%, with minimal changes in other land use types. (2) The total ESV increased by CNY 1.67 × 10⁹, with regulating services accounting for over 82%, among which water bodies contributed the most. (3) LER showed an overall increasing trend, with medium- to highest-risk areas expanding by 55.37%, lowest-risk areas increasing by 10.10%, and lower-risk areas decreasing by 65.48%. (4) Key driving factors include landscape vulnerability, vegetation coverage, and ecological land connectivity, with the influence of distance to road becoming increasingly significant. This study reveals the spatiotemporal evolution characteristics of LER in typical peri-urban villages. Based on the LERA results, combined with terrain features and ecological pressure intensity, the study area was divided into three ecological management zones: ecological conservation, ecological restoration, and ecological enhancement. Corresponding zoning strategies were proposed to guide rural ecological governance and support regional sustainable development. Full article

Understanding alpine plants’ survival and reproduction is crucial for their conservation in climate change. Based on 423 valid distribution points, this study utilizes the MaxEnt model to predict the potential habitat and distribution dynamics of Leontopodium nanum under both current and future climate scenarios, while clarifying the key factors that influence its distribution. The primary ecological drivers of distribution are altitude (2886.08 m–5576.14 m) and the mean temperature of the driest quarter (−6.60–1.55 °C). Currently, the suitable habitat area is approximately 520.28 × 10⁴ km², covering about 3.5% of the global land area, concentrated mainly in the Tibetan Plateau, with smaller regions across East and South Asia. Under future climate scenarios, low-emission (SSP126), suitable areas are projected to expand during the 2050s and 2070s. High-emission (SSP585), suitable areas may decrease by 50%, with a 66.07% reduction in highly suitable areas by the 2070s. The greatest losses are expected in the south-eastern Tibetan Plateau. Regarding dynamic habitat changes, by the 2050s, newly suitable areas will account for 51.09% of the current habitat, while 68.26% of existing habitat will become unsuitable. By the 2070s, newly suitable areas will rise to 71.86% of the current total, but the loss of existing areas will exceed these gains, particularly under the high-emission scenario. The centroid of suitable habitats is expected to shift northward, with migration distances ranging from 23.94 km to 342.42 km. The most significant shift is anticipated under the SSP126 scenario by the 2070s. This study offers valuable insights into the distribution dynamics of L. nanum and other alpine species under the context of climate change. From a conservation perspective, it is recommended to prioritize the protection and restoration of vegetation in key habitat patches or potential migration corridors, restrict overgrazing and infrastructure development, and maintain genetic diversity and dispersal capacity through assisted migration and population genetic monitoring when necessary. These measures aim to provide a robust scientific foundation for the comprehensive conservation and sustainable management of the grassland ecosystem on the Qinghai–Tibet Plateau. Full article

Road density is a key indicator of human activity, causing habitat loss and fragmentation. Soil fungi, essential for ecosystem functioning, are sensitive bioindicators. Yet their responses to road density in urban green spaces are poorly characterized. Here, we analyzed the composition of the dominant fungal community, examined both the direct and indirect effects of road density on soil fungal communities, and identified specialist species. Focusing on Shanghai, China, a rapidly urbanizing city, we considered both edaphic factor and the road network. Through machine learning and Spearman correlation regression analyses, we quantified the relative importance of road density and edaphic factor in shaping fungal community composition and employed occupancy-specificity modeling to identify specialist taxa. Our results revealed that Ascomycota, Basidiomycota, Zygomycota, Rozellomycota, Chytridiomycota, and Glomeromycota were the dominant phyla, accounting for 93% of the retrieved ITS sequences. Road density was found to be the primary driver of fungal community composition, followed by soil lead and potassium concentrations. Notably, opportunistic pathogens (Acremonium spp.) correlated positively with road density (p < 0.001). Specialist species in high-density areas were primarily pathotrophic fungi, while saprotrophic fungi dominated in low-density areas. These findings highlight the need for urban planning strategies to mitigate the ecological impact of road density. Full article

Accurate assessment of green productivity is essential for advancing sustainable agriculture in ecologically fragile regions. This study examined the evolution of agricultural green total factor productivity (AGTFP) in Tibet over the period 2002–2021 by applying a super-efficiency SBM-GML model that accounts for undesirable outputs. We decompose AGTFP into technical change and efficiency change, conduct redundancy analysis to identify sources of inefficiency and explore its spatiotemporal dynamics through kernel density estimation and convergence analysis. Results show that (1) AGTFP in Tibet grew at an average annual rate of 0.78%, slower than the national average of 1.6%; (2) labor input, livestock scale, and agricultural carbon emissions are major sources of redundancy, especially in pastoral regions; (3) technological progress is the main driver of AGTFP growth, while efficiency gains have a limited impact, reflecting a technology-led growth pattern; (4) AGTFP follows a “convergence-divergence-reconvergence” trend, with signs of conditional β convergence after controlling for regional heterogeneity. These findings highlight the need for region-specific green agricultural policies. Priority should be given to improving green technology diffusion and input allocation in high-altitude pastoral areas, alongside strengthening ecological compensation and interregional coordination to enhance green efficiency and promote high-quality development across Tibet. Full article

The Chinese red panda (Ailurus styani) is a rare and endangered animal in China; the increase in global temperature and the interference of human activities have caused irreversible effects on the suitable habitat of wild red pandas and threatened their survival. Therefore, it is necessary to carry out scientific research and protection for Chinese red pandas. In this study, the MaxEnt model was used to predict and analyze the suitable habitats of Chinese red pandas in the large and small Xiangling Mountains. The results showed that the main ecological factors affecting the suitable habitat distribution of Chinese red pandas in the Daxiangling Mountains are the average slope (45.6%, slope), the distance from the main road (24.2%, road), and the average temperature in the coldest quarter (11%, bio11). The main ecological factors affecting the suitable habitat distribution of Chinese red pandas in the Xiaoxiangling Mountains are bamboo distribution (67.4%, bamboo), annual temperature range (20.7%, bio7), and the average intensity of human activities (8.7%, Human Footprint). The predicted suitable habitat area of the Daxiangling Mountains is 123.835 km², and the predicted suitable habitat area of the Xiaoxiangling Mountains is 341.873 km². The predicted suitable habitat area of the Daxiangling Mountains accounts for 43.45% of the total mountain area, and the predicted suitable habitat area of the Xiaoxiangling Mountains accounts for 71.38%. The suitable habitat area of the Xiaoxiangling Mountains is nearly three times that of the Daxiangling Mountains, and the proportion of suitable habitat area of the Xiaoxiangling Mountains is much higher than that of the Daxiangling Mountains. The suitable habitat of Chinese red pandas in the Daxiangling Mountains is mainly distributed in the southeast, and the habitat is coherent but fragmented. The suitable habitat of Chinese red panda in Xiaoxiangling Mountains is mainly distributed in the east, and the habitat is more coherent. The results of this study can provide a scientific basis for the protection of the population and habitat of Chinese red pandas in Sichuan. Full article

This paper presents an Industrial–Ecological Symbiosis Framework that enables industrial operations to achieve quantifiable ecological gains without compromising operational efficiency. The model integrates Mixed-Integer Linear Programming (MILP) with AI-optimised forecasting to allow real-time adjustments to production and resource use. It was tested across the apparel manufacturing, metalworking, and mining sectors using publicly available benchmark datasets. The framework delivered consistent improvements: fabric waste was reduced by 10.8%, energy efficiency increased by 15%, and carbon emissions decreased by 14%. These gains were statistically validated and quantified using ecological equivalence metrics, including forest carbon sequestration rates and wetland restoration values. Outputs align with national carbon accounting systems, SDG reporting, and policy frameworks—specifically contributing to SDGs 6, 9, and 11–13. By linking industrial decisions directly to verified environmental outcomes, this study demonstrates how adaptive optimisation can support climate goals while maintaining productivity. The framework offers a reproducible, cross-sectoral solution for sustainable industrial development. Full article