Search Results (4,296)

Soybean is a vital crop supporting global food, feed, and biofuel production. Soybean yields have surged, with record yields reaching 14,678 kg/ha⁻¹, though average farm yields remain stagnant at 2770–2790 kg ha⁻¹. The persistent yield gaps leave 44% of potential production unrealized due to climate change, threatening food security. To meet future caloric demands, which are projected to rise by 46.8% by 2050, soybean breeding must prioritize climate-resilient, high-yielding varieties with minimal ecological footprints. In this comprehensive and in-depth review, we synthesized existing literature and Google Patents and reviewed the multifaceted impacts of climate-change driven eCO₂ and stresses (heat, drought, flooding, salinity, and pathogens), revealing non-linear interactions where eCO₂ may not compensate yield losses under combined stresses. We then highlight key strategies for soybean breeding under climate-change scenario. To this regard, we provide a detailed trait-by-trait breeding roadmap covering seed number, seed size, seed weight, protein-oil balance and their metabolic trade-offs, above and below ground plant architecture, nitrogen fixation and nodulation dynamics, root system architecture, water use efficiency, canopy architecture, flowering time regulation, early maturity etc., in light of specific genes and validated strategies. We explicitly discuss the novel strategies including deeper understanding of traits, abiotic stress physiology, changing pathogen dynamics, phenomics, (multi-)omics, machine learning, and modern biotechnological techniques for developing future soybean varieties. We provide a future roadmap prioritizing specific actions, including engineering climate-resilient ideotypes through gene stacking, optimizing nitrogen fixation and nutrition under stresses leveraging omics data, pan-genome, wild soybean, speeding breeding hubs, and participatory farmer-network validation, while redefining the future soybean breeder would be a hybrid orchestrator of data and dirt. This review establishes a foundational framework for translating climate-adaptive morphological, biochemical, physiological, omics, agronomic, phenomics, and biotechnological insights into actionable breeding strategies, thereby guiding policy-driven investment in soybean improvement programs targeting 2050 and beyond. Full article

Addressing climate change requires an understanding not only of science concepts but also the social, economic, and political factors that influence decision making. Thus, this study investigated the development of socio-scientific reasoning related to climate change action. This case study explored the six dimensions of socio-scientific reasoning (complexity, perspective-taking, inquiry, skepticism, affordance of science, and multiple perspective-taking) of twenty undergraduate students as they engaged with decision making about climate action. Data were collected from classroom worksheets reflecting small group decision making and individual student reflections. Data were analyzed using a rubric that categorized the level of students’ socio-scientific reasoning across the six dimensions. These categorizations were further supported by qualitative interpretation of students’ responses. The findings indicate strong performance in complexity and perspective-taking, while inquiry, skepticism, and the affordance of science were less consistently demonstrated. The study contributes to understanding how simulation-based learning can support the development of SSR and highlights the importance of structured pedagogical design in fostering higher order reasoning in climate education. Full article

Introduction: Early warning systems reduce losses when risk knowledge, forecasting, communication, and response planning operate as an end-to-end chain, yet Gulf Coast warning practice often treats hazard dynamics, ecosystem change, and social vulnerability as separate domains. This study mapped operational early warning systems for climate-relevant hazards across Louisiana, Texas, Mississippi, Alabama, and Florida and examined whether ecosystem protective functions and social vulnerability were integrated into warning thresholds, dissemination design, and preparedness planning. Methods: I conducted a scoping review using the Web of Science Core Collection and Scopus for publications from 2020 through 18 January 2026 and targeted searches of NOAA/NWS/NHC, FEMA IPAWS, CDC/ATSDR SVI, IOOS/GCOOS, USGS, and state coastal agency portals between 15 September 2025 and 18 January 2026. Of 861 identified records, 440 duplicates were removed, 421 titles and abstracts were screened, 121 full texts were assessed, and 25 sources were included in the final charting and synthesis. Results: The review identified 11 operational systems and related platforms spanning the four early warning pillars, but routine socio-ecological integration remained limited. Louisiana showed the strongest documentation of ecosystem monitoring through CPRA and CRMS, while Florida and Texas showed more developed evacuation and dissemination interfaces. Mississippi and Alabama were represented by thinner monitoring and implementation records in the included sample. Across states, ecosystem loss and social vulnerability were used more often as planning context than as repeatable inputs to thresholds, message tailoring, or assistance triggers. Discussion: Gulf Coast practices can be strengthened through formal protocols that connect ecosystem condition and vulnerability indicators to impact-based briefings, multilingual and accessible alert workflows, and tract-sensitive preparedness actions. The findings indicate that implementation can advance by linking existing datasets to defined operational decisions and by evaluating warning performance through reach, accessibility, comprehension, and action feasibility, as well as technical accuracy. Full article

The development of bioenergy crops on saline–alkaline land has been recognized as a potential pathway for both land restoration and combating global warming. However, the role of soil organic carbon (SOC) dynamics under such conditions remains insufficiently quantified in long-term assessments. In this study, an exploratory assessment was conducted to evaluate the long-term soil carbon sequestration (SCS) potential and life-cycle greenhouse gas (GHG) emissions of sustainable aviation fuel (SAF) produced from Arundo donax in the Bohai Rim region of China. The CENTURY model was integrated with Long Short-Term Memory (LSTM) time series forecasting to simulate SOC dynamics under future climate scenarios (2024–2035). Compared with the original CENTURY simulation, the LSTM model yielded a substantially more conservative estimate of SOC accumulation, with an Ensemble Mean SCS rate of 0.032 t C/ha/a and a 95% confidence interval ranging from −0.079 to 0.143 t C/ha/a. This result indicates a positive regional average tendency toward soil carbon sequestration, while also suggesting that some locations may behave as carbon sources under less favorable climatic conditions. The total SCS potential across the study area was estimated at 0.615 Tg C. When these soil carbon benefits were incorporated into the life-cycle assessment of Fischer–Tropsch (F-T) SAF, the pathway could become potentially net-negative under the adopted assumptions, reaching −32.1 g CO₂e/MJ, which corresponds to a potential reduction of 136.1% relative to fossil aviation fuel. These results should be interpreted as exploratory and scenario-based, given that large-scale cultivation of Arundo donax has not yet been established in the Bohai Rim region and the assessment therefore relies on assumptions. Beyond GHG mitigation, the cultivation of Arundo donax on degraded saline–alkaline soils may also have potential relevance to broader sustainability objectives, including SDG 13 (Climate Action) and SDG 15 (Life on Land). These findings highlight the possible synergies among energy crop cultivation, soil restoration, and climate neutrality goals, and provide preliminary insights for integrating marginal land utilization into sustainable land management and low-carbon aviation strategies. Full article

The Yeongnam wildfires in March 2025 destroyed over 40 temple halls across five Buddhist monasteries in South Korea, exposing a critical gap in wildfire management for mountain-sited cultural heritage: the existing approaches rely on static hazard maps and reactive suppression, lacking real-time terrain-aware prediction and proactive resource deployment. This study proposes a Digital Twin framework coupling high-resolution wildfire simulation with adaptive water-mist optimization to address this gap. Bogwangsa Temple (est. 949 CE, ~315 m elevation, Cheonmasan Mountain, Namyangju) serves as the case study, selected for its representative vulnerability—dense Pinus densiflora forests on steep western slopes forming a continuous fire corridor, limited vehicular access, and proximity to recent large-scale fire events. A modified Rothermel model on a 1 m cellular-automata grid, driven by a 1 m DEM, Korea Forest Service fuel data, and local weather records, simulates five scenarios from normal spring to extreme dry-wind conditions through Monte Carlo ensembles. Binary integer optimization selects the minimum-cost nozzle configuration, keeping the fire-arrival probability at four heritage structures below a safety threshold via pre-emptive activation. The adaptive deployment reduces the mean fire-arrival probability by approximately 80% compared with static sprinklers while substantially lowering water consumption. Sensitivity analyses confirm that 1 m DEM resolution captures micro-terrain features that are critical to accurate spread prediction that are lost at coarser resolutions. The modular, transferable framework contributes to SDG 11 (Sustainable Cities and Communities, Target 11.4) and SDG 13 (Climate Action). Full article

Climate change poses a significant threat to the livelihoods of smallholder farmers in South Africa, particularly in rural areas where dependence on rain-fed agriculture and limited institutional support heighten vulnerability. This study investigates how different forms of social capital (bonding, bridging, and linking) influence climate change adaptation strategies among smallholder farmers in Bergville, KwaZulu-Natal. A mixed-methods design was employed, combining a household survey (n = 150), focus group discussions, and key informant interviews. Households engaged in smallholder farming were purposively identified and randomly selected within the study ward. To accommodate varying literacy levels, structured questionnaires were administered through interviewer-led surveys. Quantitative data were analysed using descriptive statistics, chi-square tests, and a probit regression model, while qualitative data were thematically analysed to contextualise adaptation decisions and social dynamics. The findings show that trust in peer information, farmer group membership, collective action, and access to extension services significantly increase the likelihood of adopting climate adaptation practices (p < 0.05). While bonding social capital supports short-term coping, limited bridging and linking social capital constrain access to institutional resources and climate information. By explicitly operationalising and empirically distinguishing these dimensions of social capital, the study provides context-specific evidence on how uneven social networks shape adaptation outcomes. Strengthening inclusive institutional linkages and extension services is essential for promoting long-term climate resilience among smallholder farmers in rural South Africa. This study contributes to the international literature by providing empirical evidence on the differentiated roles of social capital dimensions in shaping adaptation outcomes in resource-constrained rural contexts. The findings highlight the need for policy interventions that strengthen institutional linkages, improve extension service delivery, and promote inclusive access to adaptation resources to enhance long-term climate resilience. Full article

Urban areas are increasingly exposed to water-related challenges, including flood risk and water scarcity, amplified by climate change, population growth, and extensive soil sealing. Addressing these pressures requires integrated stormwater management (SWM) strategies that balance hydraulic, environmental, and social objectives. This study introduces a novel, replicable Key Performance Indicator (KPI)-based assessment framework for 36 green–blue and grey sustainable stormwater management systems (SWMSs), designed to enable cross-typology, multiscale comparison. Six KPIs, encompassing flood regulation, water consumption, water quality, air quality, environmental amenity, and biodiversity potential, are derived through a critical synthesis and harmonisation of the literature and complemented with new parameters and sub-parameters to address existing methodological gaps. The framework structures evaluations into six analytical tables and one summary table, ensuring transparent, systematic, and comparative assessment of heterogeneous solutions. Application to a pilot project in Rome demonstrates how integrating KPI evaluation with parametric hydraulic modelling provides actionable insights for solution selection. It also facilitates identification of potential synergies between performance dimensions, enhancing its value as a decision-support tool in preliminary design. Overall, the study demonstrates the research value of multi-scalar, performance-based approaches for urban water planning, highlights the transferability of resilient stormwater strategies in climate-sensitive contexts, and identifies promising avenues for future research, including multi-sectoral integration, trade-off analysis, and cross-platform application. Full article

Utilizing MODIS LST data from 2003 to 2024, in conjunction with multi-source remote sensing data including DEM, land use, NDVI, and nighttime lights, this study conducts a remote sensing quantitative assessment and spatiotemporal characteristic analysis of the urban heat island (UHI) effect in Yinchuan City. An improved urban-rural dichotomy approach was adopted to select rural background areas, and elevation correction of land surface temperature was performed based on the zonal ordinary least squares (OLS) regression to eliminate systematic errors caused by topographic differences. The results show that: (1) From 2003 to 2024, the overall intensity of the UHI in Yinchuan City showed a slight downward trend, while the UHI area continued to expand, presenting the characteristics of “decreasing intensity and expanding scope”; (2) The UHI exhibited concentrated and contiguous distribution in summer, and the cold island phenomenon was significant in winter, reflecting the typical seasonal contrast between summer and winter; (3) The global Moran’s I value increased from 0.39 to 0.82, indicating a significant enhancement in the spatial agglomeration of the UHI; (4) The standard deviation ellipse analysis revealed that the centroid of the UHI migrated toward the westward as a whole, which was consistent with the main axis of urban construction. The research results reveal the long-term evolution law and spatial pattern characteristics of the UHI effect in Yinchuan City, and provide a scientific reference for ecological planning and thermal environment regulation of cities in arid regions. These findings enhance the understanding of long-term urban thermal environment dynamics and provide important scientific support for sustainable urban planning, climate adaptation, and ecological management in arid regions. The study contributes to the quantitative monitoring of urban environmental sustainability and supports sustainable development goals related to climate action and sustainable cities. Full article

This study adopts the theory of planned behavior to investigate consumers’ purchasing decisions under extreme weather conditions. Specifically, this paper examines how extreme global weather events motivate consumers to consider purchasing green products and prioritize environmental sustainability in their consumption choices. It further explores whether consumers’ adoption of green products enhances their satisfaction under abnormal global climate conditions, as well as how consumer satisfaction subsequently improves individuals’ mood, anxiety, and cognitive states. Structural equation modeling was employed to test the hypothesized model using data collected from 352 valid respondents in China. As the global community strives to achieve net-zero CO₂ emissions by 2050, numerous firms and manufacturers have incorporated green product concepts to advance sustainable operations. The empirical results reveal that anxiety and cognition are positively related to green purchasing decisions, which in turn exert a positive influence on consumer satisfaction. Based on these findings, this study proposes actionable strategies to promote green consumption behavior by accounting for relevant psychological factors. Full article

Rapid urbanisation and climate change are intensifying urban heat stress, posing significant challenges for climate-responsive urban planning. Digital and data-driven approaches, including GIS, remote sensing, microclimate simulation, and artificial intelligence (AI), have advanced urban climate analysis; however, their capacity to support human-centred planning remains insufficiently synthesised. This review analyses 78 peer-reviewed studies (2015–2025) to evaluate how digital methods address urban microclimate and outdoor thermal comfort. The reviewed studies are classified into four methodological groups: spatial data analytics, simulation-based models, parametric and optimisation workflows, and AI-driven or hybrid approaches. The results show that the majority of studies rely on proxy indicators, such as land surface temperature and sky view factor, while physiologically based comfort indices (e.g., PET and UTCI) are applied in a limited proportion of studies and remain largely confined to microscale simulations. A persistent scale mismatch is identified between large-scale analytics and pedestrian-level thermal experience, alongside geographic and climatic biases, particularly in hot-arid regions. Unlike previous reviews, this study integrates digital methodologies, urban microclimate processes, and human-centred thermal comfort within a unified framework. The findings provide actionable insights for planners and designers by supporting the integration of thermal comfort into multi-scale, climate-responsive decision-making. Full article

This short communication synthesizes evidence on how the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) altimetry data are used by private sector actors and the implications for economic value creation. Using secondary research that collected and summarized information from existing data from reports, journals, websites, and databases, the work identifies 54 companies across 9 sectors leveraging ICESat-2-derived elevation, canopy height, bathymetry, and surface measurements to inform decision-making, risk assessment, and new business models. The analysis situates ICESat-2 within a broader context where freely available Earth observation data can generate substantial private- and public-sector value, potentially exceeding hundreds of billions in aggregate when scaled across industries such as geospatial services, climate management, real estate, and insurance. The paper uses a four-pillar conceptual model to guide valuation of data-driven impacts: Data Utility (intrinsic information value of altimetry and related metrics), Decision Impact (tangible economic benefits from improved models and operations), Strategic Integration (emergence of new business models and market opportunities), and Data Ecosystem Exclusivity (development of proprietary datasets and workflows that enable competitive differentiation). Empirical findings illustrate how these pillars manifest in practice. The paper seeks to connect private-sector uptake to NASA’s Earth Science to Action framework and related capacity-building efforts, highlighting pathways for broader utilization through training, tutorials, and accessible interfaces. Limitations of the study include partial sector coverage and reliance on publicly reported use cases. Future work should quantify economic returns with standardized metrics and extend the dataset to capture dynamic shifts in data products, governance, and IP development within the evolving data ecosystem. Full article

Sustainability and the Sustainable Development Goals (SDGs) are garnering significant attention due to growing global challenges, including poverty, inequality, environmental degradation, and climate change, with the latter addressed specifically through SDG 13. This study examined the level of self-reported awareness of six science-related SDGs—SDG 3 (Good Health and Well-Being), SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and Clean Energy), SDG 13 (Climate Action), SDG 14 (Life Below Water), and SDG 15 (Life on Land)—among science teachers in the Arab sector in Israel as a function of background variables: gender, seniority, degree type, academic institution, school type, area of specialization, and the integration of these SDGs into the science curriculum. The study employed a mixed-methods approach: in the quantitative component, 204 science teachers responded to a Likert-scale questionnaire; the qualitative component consisted of semi-structured interviews with 30 middle school science teachers from the Arab sector. The findings indicated a moderate level of self-assessed awareness regarding SDGs. Significant differences in awareness were found according to teaching subject: environmental studies teachers demonstrated the highest awareness, followed by general science, biology, and physics teachers, with chemistry teachers ranking lowest. No significant differences were found for the remaining variables (p > 0.05). Qualitative findings indicated that while teachers perceived SDG-related content as implicitly present in the curriculum, explicit and systematic integration of the SDG framework is largely absent. Overall, the findings suggest that teachers are not adequately exposed to the SDGs. Therefore, it is recommended to incorporate these topics into teacher-training courses and professional development programs and to further integrate them into curricula. This study contributes to the growing body of research on SDG integration in science education, particularly within underexplored minority educational contexts. Full article

Globally, the combined pollution of fine particulate matter (PM_2.5) and ground-level ozone (O₃) poses severe challenges to public health and sustainable urban development. Recent data indicate that the annual average PM_2.5 concentration in the vast majority of cities worldwide fails to meet World Health Organization safety standards, with air pollution causing millions of premature deaths annually. As a nature-based solution, the purification efficacy of vegetation remains poorly quantified due to unclear coupling mechanisms with local meteorological conditions. This study systematically reviewed and synthesized 229 empirical studies published between 2000 and 2025 from Web of Science and China National Knowledge Infrastructure (CNKI), aiming to clarify the quantitative relationships and regulatory mechanisms of plant–meteorological synergistic purification of PM_2.5–O₃. Following double-blind independent screening (κ = 0.85) and data extraction, a quantitative minimal feasible synthesis approach was adopted due to high data heterogeneity. The results indicated the following. (1) The median canopy purification efficiency of urban vegetation for PM_2.5 was 18.2% (IQR: 12.5–30.1%, n = 17), with a median dry deposition velocity (Vd–PM) of 0.05 cm s⁻¹ (0.02–30 cm s⁻¹, n = 15). The median dry deposition velocity (Vd–O₃) for O₃ was 0.55 cm s⁻¹ (0.12–1.82 cm s⁻¹, n = 8), with non-stomatal deposition contributing approximately 35%. (2) Meteorological factors exhibit nonlinear regulation: relative humidity (RH) > 70% significantly enhances PM_2.5 adsorption, wind speeds of 1.5–3.0 m s⁻¹ are optimal for PM_2.5 deposition, and temperatures > 30 °C generally inhibit plant uptake of both pollutants (n = 7). (3) Functional traits strongly correlate with purification efficacy: species with high leaf roughness (R² = 0.8), high stomatal conductance, and low BVOC emissions (e.g., Ginkgo biloba, Platycladus orientalis) exhibit optimal synergistic purification potential. Species with high BVOC emissions (Populus przewalskii, Eucalyptus robusta) can increase daily net O₃ pollution equivalents by up to 86 g and must be strictly avoided. Based on quantitative evidence, a green space planning decision matrix indexed by climate zone and pollution type was developed, specifying vegetation configuration patterns, functional group selection, and key design parameters (canopy closure, green belt width, etc.) for different scenarios. This study provides an actionable scientific basis for precision planning and climate-adaptive management of urban green infrastructure. Full article

In Europe, the most valuable grasslands are semi-natural ecosystems maintained by long-term extensive human management, particularly pastoralism, and therefore do not represent climax vegetation. According to the Natura 2000 habitat interpretation manual (EUR-28), key habitats include xerothermic grasslands of Festuco-Brometalia (code 6210*) on calcareous soils and sandy grasslands of Koelerion glaucae (code 6120*) on poor substrates. Only 10–15% of their area in the EU has favorable conservation status. The main threat is secondary succession and encroachment (83.94%), caused by abandonment of traditional management (81.75%). Without mowing or grazing, dominant grasses replace rare species, followed by shrubs and trees. Other pressures include intensive agriculture (75.18%), habitat loss and fragmentation (69.34%), climate change (37.96%), invasive species (23.36%) and urbanization (14.60%). Multiple threats often co-occur, so cumulative percentages exceed 100%. The most effective conservation method is restoring or maintaining extensive grazing, particularly with local sheep and goat breeds. Grazing limits succession, increases structural diversity and promotes seed dispersal, creating a mosaic of microhabitats that enhances biodiversity. Effective protection requires landscape-scale actions, limiting urban development, and long-term support for farmers under the Common Agricultural Policy. Increasing public awareness of the ecological and cultural value of these ecosystems is also essential. Full article

Urban areas are pivotal to achieving the Sustainable Development Goals (SDGs), yet sustainability monitoring at the municipal level remains fragmented, difficult to operationalize, and weakly comparable across cities. Although the SDGs provide a comprehensive global agenda and ISO 37120 offers a standardized set of city indicators, municipalities still face practical barriers in translating global targets into actionable, jurisdiction-sensitive, and measurable metrics aligned with local responsibilities and available data. This study addresses this gap by presenting the design of an integrated, target-level urban sustainability assessment framework grounded in SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) principles and explicitly tailored to municipalities in developed-country contexts. The framework contributes (i) a structured procedure for disaggregating and reallocating SDG targets according to municipal responsibilities, (ii) a six-dimension architecture that consolidates SDG targets and ISO 37120 themes into a coherent, governance-oriented structure (Government and Economic Development; Civic & Social Infrastructure; Environment and Climate; Infrastructure and Urban Planning; Health; Urban Living Conditions), and (iii) a SMART-based indicator screening logic that prioritizes feasibility, data availability, and benchmarking potential, thus supporting the green transition in Urban Areas. The framework is empirically examined through validation against sustainability reporting practices of the Porto City Council, quantifying indicator coverage, assessing alignment with municipal mandates, and identifying systematic gaps—particularly in cross-cutting areas such as governance transparency, equity monitoring, and long-term climate adaptation. Overall, the results indicate that the proposed approach strengthens coherence, measurability, and comparability in urban sustainability assessment, supporting evidence-based municipal decision-making, performance benchmarking, and more strategically aligned SDG localization. Full article