Search Results (493)

Climate warming is anticipated to significantly alter the distribution and composition of plant species in the Arctic, thereby cascading through food webs and affecting both associated fauna and entire ecosystems. To elucidate the trend in plant distribution in response to climate change, we employed the MaxEnt model to project the future ranges of 25 representative Arctic and Circumpolar plant species (including grasses and shrubs). Species distribution data, in conjunction with bioclimatic variables derived from climate projections of three selected General Circulation Models (GCMs), ESM2, IPSl, and MPIE, were utilized to fit the MaxEnt models. Subsequently, we predicted the potential distributions of these species under three Shared Socioeconomic Pathways (SSPs)—SSP126, SSP245, and SSP585—across a timeline spanning 2010, 2050, 2100, 2200, 2250, and 2300 AD. Range shift indices were applied to quantify changes in plant distribution and range sizes. Our results show that the ranges of nearly all species are projected to diminish progressively over time, with a more pronounced rate of reduction under higher emission scenarios. The species are generally expected to shift northward, with the distances of these shifts positively correlated with both the time intervals from the current state and the intensity of thermal forcing associated with the SSPs. Arctic species (A_Spps) are anticipated to face higher extinction risks compared to Boreal–Arctic species (B_Spps). Additional indices, such as range gain, loss, and overlap, consistently corroborate these patterns. Notably, the peak range shift speeds differ markedly between SSP245 and SSP585, with the latter extending beyond 2100 AD. In conclusion, under all SSPs, A_Spps are generally expected to experience more significant range shifts than B_Spps. In the SSP585 scenario all species are projected to face substantial range reductions, with Arctic species being more severely affected and consequently facing the highest extinction risks. These findings provide valuable insights for developing conservation recommendations for polar plant species and have significant ecological and socioeconomic implications. Full article

Numerous studies have demonstrated that in residential areas of Western cities, both luxury and legacy effects significantly shape tree species diversity dynamics. However, the specific mechanisms driving these diversity patterns in China, where urbanization has progressed at an unprecedented pace, remain poorly understood. In this study we selected 20 residential settlements and 7 key socio-economic properties to investigate the change trend of tree diversity (2006–2021) and its socio-economic driving factors in Beijing. Our results demonstrate significant increases in total, native, and exotic tree species richness between 2006 and 2021 (p < 0.05), with average increases of 36%, 26%, and 55%, respectively. Total and exotic tree Shannon-Wiener indices, as well as exotic tree Simpson’s index, were also significantly higher in 2021 (p < 0.05). Housing prices was the dominant driver shaping total and exotic tree diversity, showing significant positive correlations with both metrics. In contrast, native tree diversity exhibited a strong positive association with neighborhood age. Our findings highlight two dominant mechanisms: legacy effect, where older neighborhoods preserve native diversity through historical planting practices, and luxury effect, where affluent communities drive exotic species proliferation through ornamental landscaping initiatives. These findings elucidate the dual dynamics of legacy conservation and luxury-driven cultivation in urban forest development, revealing how historical contingencies and contemporary socioeconomic forces jointly shape tree diversity patterns in urban ecosystems. Full article

The water-yield function in the Yellow River Basin (YRB) of China for maintaining the basin’s ecological water balance plays a crucial role. Understanding its spatiotemporal variation and the underlying drivers in the basin is crucial for the management, utilization, and development of water resources. Thus, we used the InVEST model to explore its spatiotemporal dynamics across multiple scales (“basin–county–pixel”). Then, we integrated socio-economic and natural factors to elucidate the driving forces and spatial heterogeneity of water-yield dynamics. Our findings indicated that water-yield trends increased in 71.76% of the YRB, and significant water-yield increases were detected in 13.9% of the basin over the past 40 years. A phase-wise comparison revealed a shift in water yield from a decreasing trend in the first two decades to a significant increasing trend in the last two decades. Hotspot analysis revealed that hotspots of increasing water-yield trends have shifted from the downstream section of the basin toward the southwest, while hotspots of decreasing water-yield trends first concentrated in the basin’s southern part and then disappeared. Both natural and socioeconomic factors have exerted positive and negative impacts on water-yield dynamics. Among them, the dynamics of water yield have been predominantly driven by natural variables. Full article

Global policy narratives on livestock development increasingly emphasize environmental concerns, often overlooking the social dimensions of the sector. In the case of dairy, the world’s most valuable agricultural commodity, its role in social and economic development remains poorly quantified. Our study contributes to a more balanced vision of the UN SDGs thanks to the inclusion of a socio-economic dimension. Here we present a novel empirical approach to assess the socio-economic impacts of dairy development using a new global dataset and non-parametric modelling techniques (local polynomial regressions), with yield as a proxy for sectoral performance. We find that as dairy systems intensify, the number of farm households engaged in production declines, yet household incomes rise. On-farm labour productivity also increases, accompanied by a reduction in employment but higher wages. In dairy processing, employment initially grows, peaks, and then contracts, again with rising wages. The most substantial impact is observed among consumers: an increased milk supply leads to lower prices and improved affordability, expanding the access to dairy products. Additionally, dairy development is associated with greater agricultural value added, an expanding tax base, and the increased formalization of the economy. These findings suggest that dairy development, beyond its environmental footprint, plays a significant and largely positive role in social transformation, yet is having to adapt sustainably while tackling labour force relocation, and that dairy development’s social impacts mimic the general agricultural sector. These results might be of interest for the assessment of policies regarding dairy development. Full article

Urban expansion has a profound impact on both society and the environment. In this study, VOSviewer 1.6.16 and CiteSpace 6.3.R1 were used to conduct a bibliometric analysis of 2987 articles published during the period of 1992–2022 from the Web of Science database in order to identify the research hotspots and trends of urban expansion and its driving factors. The number of articles significantly increased during the period of 1992–2022. The spatiotemporal characteristics and driving forces of urban expansion, urban growth models and simulations, and the impacts of urban expansion were the main research topics. The rate of urban expansion showed regional differences. Socioeconomic factors, political and institutional factors, natural factors, path effects, and proximity effects were the main driving factors. Urban expansion promoted economic growth, occupied cultivated land, and affected ecological environments. Big data and deep learning techniques were recently applied due to advancements in information techniques. With the increasing awareness of environmental protection, the number of studies on environmental impacts and spatial planning regulations has increased. Some political and institutional factors, such as subsidies, taxation, spatial planning, new development strategies, regulation policies, and economic industries, had controversial or unknown impacts. Further research on these factors and their mechanisms is needed. A limitation of this study is that articles which were not indexed, were not included in bibliometric analysis. Further studies can review these articles and conduct comparative research to capture the diversity. Full article

Modern utilities face unprecedented pressures as trends in digital transformation and democratized energy choice empower consumers to engage in peak shaving, flexible load management, and adopt grid automation and intelligence solutions. A powerful confluence of architectural, technological, and socio-economic forces is transforming the U.S. electricity market, triggering significant changes in electricity production, transmission, and consumption. Utilities are embracing digital twins and repurposed Utility 2.0 concepts—distributed energy resources, microgrids, innovative electricity market designs, real-time automated monitoring, smart meters, machine learning, artificial intelligence, and advanced data and predictive analytics—to foster operational flexibility and market efficiency. This analysis qualitatively evaluates how digitalization, Battery Energy Storage Systems (BESSs), and adaptive strategies to mitigate rebound effects collectively advance smart duck curve management. By leveraging digital platforms for real-time monitoring and predictive analytics, utilities can optimize energy flows and make data-driven decisions. BESS technologies capture surplus renewable energy during off-peak periods and discharge it when demand spikes, thereby smoothing grid fluctuations. This review explores the benefits of targeted digital transformation, BESSs, and managed rebound effects in mitigating the duck curve problem, ensuring that energy efficiency gains translate into actual savings. Furthermore, this integrated approach not only reduces energy wastage and lowers operational costs but also enhances grid resilience, establishing a robust framework for sustainable energy management in an evolving market landscape. Full article

The rapid rise of the silver economy in the new era has become a new driving force for socio-economic development. From the perspective of Marxist political economy theory, this paper analyzes the intrinsic logic of the silver economy’s development through three dimensions: surplus value, labor market, and capital. The study finds that the silver economy in the new era faces challenges such as insufficient supply of high-quality elderly care services, simultaneous shortages in both total talent quantity and structural imbalances, and contradictions between capital’s profit-seeking nature and social welfare. By introducing the multiple streams model, the paper elucidates the coupling process of these three streams and the timing of policy window openings. It proposes targeted strategies, including strengthening technological innovation, deepening labor market reforms, and optimizing capital allocation, to promote the robust development of China’s silver economy and inject strong momentum into sustainable and high-quality economic growth. Full article

Under global warming, persistent extreme heat events (PHEs) in China have increased significantly in both frequency and intensity, posing severe threats to agriculture and socioeconomic development. Combining observational analysis (1961–2019) and numerical simulations, this study investigates the distinct impacts of Northwest Pacific (NWP) and North Atlantic (NA) sea surface temperature (SST) anomalies on PHEs over China. Key findings include the following: (1) PHEs exhibit heterogeneous spatial distribution, with the Yangtze-Huai River Valley as the hotspot showing the highest frequency and intensity. A regime shift occurred post-2000, marked by a threefold increase in extreme indices (+3σ to +4σ). (2) Observational analyses reveal significant but independent correlations between PHEs and SST anomalies in the tropical NWP and mid-high latitude NA. (3) Numerical experiments demonstrate that NWP warming triggers a meridional dipole response (warming in southern China vs. cooling in the north) via the Pacific–Japan teleconnection pattern, characterized by an eastward-retreated and southward-shifted sub-tropical high (WPSH) coupled with an intensified South Asian High (SAH). In contrast, NA warming induces uniform warming across eastern China through a Eurasian Rossby wave train that modulates the WPSH northward. (4) Thermodynamically, NWP forcing dominates via asymmetric vertical motion and advection processes, while NA forcing primarily enhances large-scale subsidence and shortwave radiation. This study elucidates region-specific oceanic drivers of extreme heat, advancing mechanistic understanding for improved heatwave predictability. Full article

Property crime is a pressing issue in maintaining social order and urban sustainability, particularly in regions marked by pronounced socioeconomic disparity. While the link between socioeconomic stress and crime is well established, regional variations in Thailand have not been fully examined. Therefore, the purpose of this research was to examine spatial patterns of property crime and identify the potential associations between property crime and socioeconomic environment across Thailand. Using nationally compiled property-crime data from official sources across all provinces of Thailand, we employed geographic information system (GIS) tools to conduct a spatial cluster analysis at the sub-national level across 76 provinces. Both global and local statistical techniques were applied to identify spatial associations between property-crime rates and neighborhood-level socioeconomic conditions. The results revealed that property-crime clusters are primarily concentrated in the south, while low-crime areas dominate parts of the north and northeast regions. To analyze the spatial dynamics of property crime, we used geospatial statistical models to investigate the influence of socioeconomic variables across provinces. We found that property-crime rates were significantly associated with monthly income, areas experiencing high levels of household debt, migrant populations, working-age populations, an uneducated labor force, and population density. Identifying associated factors and mapping geographic regions with significant spatial clusters is an effective approach for determining where issues concentrate and for deepening understanding of the underlying patterns and drivers of property crime. This study offers actionable insights for enhancing safety, resilience, and urban sustainability in Thailand’s diverse regional contexts by highlighting geographies of vulnerability. Full article

The remote sensing monitoring of land use changes and future scenario simulation hold crucial significance for accurately characterizing urban expansion patterns, optimizing urban land use configurations, and thereby promoting coordinated regional development. Through the integration of multi-source data, this study systematically analyzes the spatiotemporal trajectories and driving forces of land use changes in the Pearl River Delta urban agglomeration (PRD) from 1990 to 2020 and further simulates the spatial patterns of urban land use under diverse development scenarios from 2025 to 2035. The results indicate the following: (1) During 1990–2020, urban expansion in the Pearl River Delta urban agglomeration exhibited a “stepwise growth” pattern, with an annual expansion rate of 3.7%. Regional land use remained dominated by forest (accounting for over 50%), while construction land surged from 6.5% to 21.8% of total land cover. The gravity center trajectory shifted southeastward. Concurrently, cropland fragmentation has intensified, accompanied by deteriorating connectivity of ecological lands. (2) Urban expansion in the PRD arises from synergistic interactions between natural and socioeconomic drivers. The Geographically and Temporally Weighted Regression (GTWR) model revealed that natural constraints—elevation (regression coefficients ranging −0.35 to −0.05) and river network density (−0.47 to −0.15)—exhibited significant spatial heterogeneity. Socioeconomic drivers dominated by year-end paved road area (0.26–0.28) and foreign direct investment (0.03–0.11) emerged as core expansion catalysts. Geographic detector analysis demonstrated pronounced interaction effects: all factor pairs exhibited either two-factor enhancement or nonlinear enhancement effects, with interaction explanatory power surpassing individual factors. (3) Validation of the Patch-generating Land Use Simulation (PLUS) model showed high reliability (Kappa coefficient = 0.9205, overall accuracy = 95.9%). Under the Natural Development Scenario, construction land would exceed the ecological security baseline, causing 408.60 km² of ecological space loss; Under the Ecological Protection Scenario, mandatory control boundaries could reduce cropland and forest loss by 3.04%, albeit with unused land development intensity rising to 24.09%; Under the Economic Development Scenario, cross-city contiguous development zones along the Pearl River Estuary would emerge, with land development intensity peaking in Guangzhou–Foshan and Shenzhen–Dongguan border areas. This study deciphers the spatiotemporal dynamics, driving mechanisms, and scenario outcomes of urban agglomeration expansion, providing critical insights for formulating regionally differentiated policies. Full article

Over the past few decades, occurrences of extreme climatic events have escalated significantly, with severe repercussions for global ecosystems and socio-economics. northern China (NC), characterized by its complex topography and diverse climatic conditions, represents a typical ecologically vulnerable region where vegetation is highly sensitive to climate change. Therefore, monitoring vegetation dynamics and analyzing the influence of extreme climatic events on vegetation are crucial for ecological conservation efforts in NC. Based on extreme climate indicators and the Normalized Difference Vegetation Index (NDVI), this study employed trend analysis, Ensemble Empirical Mode Decomposition, all subsets regression analysis, and random forest to quantitatively investigate the spatiotemporal variations in historical and projected future NDVI trends in NC, as well as their responses to extreme climatic conditions. The results indicate that from 1982 to 2018, the NDVI in NC generally exhibited a recovery trend, with an average growth rate of 0.003/a and a short-term variation cycle of approximately 3 years. Vegetation restoration across most areas was primarily driven by short-term high temperatures and long-term precipitation patterns. Future projections under different emission scenarios (SSP245 and SSP585) suggest that extreme climate change will continue to follow historical trends. However, increased radiative forcing is expected to constrain both the rate of vegetation growth and its spatial expansion. These findings provide a scientific basis for mitigating the impacts of climate anomalies and improving ecological quality in NC. Full article

In a warming climate, rising temperature are expected to influence atmospheric humidity. This study examined the spatio-temporal dynamics of temperature (TEMP) and relative humidity (RH) across Equatorial Africa from 1980 to 2020. The analysis used RH data from European Centre of Medium-range Weather Forecasts Reanalysis v.5 (ERA5) reanalysis, TEMP and precipitation (PRE) from Climate Research Unit (CRU), and soil moisture (SM) and evapotranspiration (ET) from the Global Land Evaporation Amsterdam Model (GLEAM). In addition, four teleconnection indices were considered: El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO). This study used the Mann–Kendall test and Sen’s slope estimator to analyze trends, alongside multiple linear regression to investigate the relationships between TEMP, RH, and key climatic variables—namely evapotranspiration (ET), soil moisture (SM), and precipitation (PRE)—as well as large-scale teleconnection indices (e.g., IOD, ENSO, PDO, and NAO) on annual and seasonal scales. The key findings are as follows: (1) mean annual TEMP exceeding 30 °C and RH less than 30% were concentrated in arid regions of the Sahelian–Sudano belt in West Africa (WAF), Central Africa (CAF) and North East Africa (NEAF). Semi-arid regions in the Sahelian–Guinean belt recorded moderate TEMP (25–30 °C) and RH (30–60%), while the Guinean coastal belt and Congo Basin experienced cooler, more humid conditions (TEMP < 20 °C, RH (60–90%). (2) Trend analysis using Mann–Kendal and Sen slope estimator analysis revealed spatial heterogeneity, with increasing TEMP and deceasing RH trends varying by region and season. (3) The warming rate was higher in arid and semi-arid areas, with seasonal rates exceeding annual averages (0.18 °C decade⁻¹). Winter (0.27 °C decade⁻¹) and spring (0.20 °C decade⁻¹) exhibited the strongest warming, followed by autumn (0.18 °C decade⁻¹) and summer (0.10 °C decade⁻¹). (4) RH trends showed stronger seasonal decline compared to annual changes, with reduction ranging from 5 to 10% per decade in certain seasons, and about 2% per decade annually. (5) Pearson correlation analysis demonstrated a strong negative relationship between TEMP and RH with a correlation coefficient of r = − 0.60. (6) Significant associations were also observed between TEMP/RH and both climatic variables (ET, SM, PRE) and large scale-teleconnection indices (ENSO, IOD, PDO, NAO), indicating that surface conditions may reflect a combination of local response and remote climate influences. However, further analysis is needed to distinguish the extent to which local variability is independently driven versus being a response to large-scale forcing. Overall, this research highlights the physical mechanism linking TEMP and RH trends and their climatic drivers, offering insights into how these changes may impact different ecological and socio-economic sectors. Full article

As an ecological transition zone, the ecosystem of the Qin River Basin in the middle reaches of the Yellow River is of great significance to the regional ecological balance. With the rapid socio-economic development, land use changes are significant, and the spatial and temporal patterns of ecosystems are evolving. Exploring its dynamics and driving mechanisms is crucial to the ecological protection and sustainable development of watersheds. This research systematically examines the spatiotemporal dynamics and driving mechanisms of ecosystem patterns in the middle Yellow River’s Qin River Basin (1990–2020). Quantitative assessments integrating ecosystem transition metrics and redundancy analysis reveal three critical insights: (1) dominance of agricultural land and woodland (74.81% combined coverage), with grassland (18.58%) and other land types (6.61%) constituting secondary components; (2) dynamic interconversion between woodland and grassland accompanied by urban encroachment on agricultural land, manifesting as net reductions in woodland (−13.74%), farmland (−6.60%), and wetland (−38.64%) contrasting with grassland (+43.34%) and built-up area (+116.63%) expansion; (3) quantified anthropogenic drivers showing agricultural intensification (45.03%) and ecological protection measures (36.50%) as primary forces, while urbanization account for 18.47% of observed changes. The first two RDA ordination axes significantly (p < 0.01) explain 68.3% of the variance in ecosystem evolution, particularly linking land-use changes to socioeconomic indicators. Based on these findings, the study proposes integrated watershed management strategies emphasizing scientific land-use optimization, controlled urban expansion, and systematic ecological rehabilitation to enhance landscape stability in this ecologically sensitive region. The conclusions of this study have important reference value for other ecologically sensitive watersheds in land use planning, ecological protection policy making, and ecological restoration practice, which can provide a theoretical basis and practical guidance. Full article

Accelerating climate change poses significant risks to water security and ecological stability in arid regions due to the increasing frequency and intensity of extreme precipitation events. As a climate-sensitive area, the inland river basin (IRB) of Northwest China—a critical water source for local ecosystems and socioeconomic activities—remains insufficiently studied in terms of future extreme precipitation dynamics. This study evaluated the spatiotemporal evolution of extreme precipitation in the IRB under a new low radiative forcing scenario (SSP1-1.9) by employing four global climate models (GCMs: GFDL-ESM4, MRI-ESM2, MIROC6, and IPSL-CM6A-LR). Eight core extreme precipitation indices were analyzed to quantify changes during the near future (NF: 2021–2050) and far future (FF: 2071–2100) periods. Our research demonstrated that all four models were capable of capturing seasonal patterns and exhibited inherent uncertainty. The annual total precipitation (PRCPTOT) in mountainous regions showed minimal variation, while desert areas were projected to experience a 2-6-fold increase in precipitation in the NF and FF. The Precipitation Intensity Index (SDII) weakened by approximately −10% in mountainous areas but strengthened by around +10% in desert regions. Most mountainous areas showed an increase in the maximum consecutive dry days (CDD), whereas desert regions exhibited extended maximum consecutive wet days (CWD). Moderate rainfall (P1025) variations primarily ranged between −5% and +20%, with greater fluctuations in desert areas. Heavy rainfall (PG25) fluctuated between −40% and +40%, reflecting stark contrasts in extreme precipitation between arid basins and mountainous zones. The maximum 1-day precipitation (Rx1day) and maximum 5-day precipitation (Rx5day) both showed significant increases, which indicated heightened risks from extreme rainfall events in the future. Moreover, the IRB region experienced increased total precipitation, enhanced rainfall intensity, more frequent alternations between drought and precipitation, more frequent moderate-to-heavy rainfall days, and higher daily precipitation extremes in both the NF and FF periods. These findings provide critical data for regional development planning and emergency response strategy formulation. Full article

The B Corp certification is a voluntary designation granted by B Lab. This nonprofit organization evaluates two main aspects of a company’s operations: the positive impact generated by its daily activities and how its business model reflects unique practices that yield positive outcomes for its stakeholders. Sistema B is at the forefront of the B movement in Latin America and the Caribbean, working to develop an ecosystem that enables B Corps to harness market forces to address social and environmental challenges. However, the B Corp movement in this region faces significant challenges, primarily due to a lack of government support, including tax benefits and legal recognition. This study aims to advance the existing literature on B Corps by examining sustainability-oriented hybrid organizations that strive to reconcile profit generation with social impact within the context of Mexico’s socioeconomic landscape. Additionally, it seeks to enhance the understanding of how ventures navigate trade-offs between financial and social objectives, and to identify factors that can help address these challenges. Twenty semi-structured interviews were conducted with Mexican B Corps to explore the entrepreneurial motivations related to social objectives, the B Corp movement, and the internal organizational dynamics of balancing social and economic logics. We discuss how tensions arise and are managed, as well as the issues regarding regulatory tensions in Mexico and the challenges that stem from organizational complexities. Future research directions are also outlined. Full article