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Soil microbial diversity is crucial to sustaining ecosystem productivity and improving carbon sequestration. Global temperature continues to rise, but how climate warming affects microbial diversity and its capacity to sequester soil organic carbon (SOC) remains uncertain. Here, by conducting a global meta-analysis with 251 paired observations from 102 studies, we showed that, on average, warming reduced bacterial and fungal diversity (measured by richness and Shannon index) by 16.0 and 19.7%, respectively, and SOC by 18.1%. The negative responses of both soil bacterial and fungal diversity to warming became more pronounced with increasing warming magnitude, experimental duration, and decreasing soil nitrogen availability. Under the worst-case climate warming scenario (2010 to 2070, 3.4 increase in °C), soil bacterial diversity and fungal diversity are projected to reduce by 56% and 81%, respectively, over 60 y. Importantly, in addition to the direct impact of warming on SOC, warming-induced declines in microbial diversity also contributed to SOC losses. We highlight that prolonged warming could substantially reduce soil microbial diversity and decrease SOC sequestration, accelerating future warming and underscoring the urgent need for decisive actions to mitigate global climate change. 

Virtual site visits are increasingly becoming a viable educational tool for educators to supplement or replace traditional visits when these are challenged by logistical issues, inaccessibility, or safety hazards. Recent research has explored the integration of theory-based learning strategies, such as collaborative problem-solving and multimedia learning, in online construction site visits to support construction students’ collaborative skill development and learning effectiveness. However, there remains a lack of understanding of how to guide students systematically from conceptual knowledge to more complex, hands-on, or procedural knowledge, which often leads to a fragmented learning experience in current online site visit designs. This study aims to integrate active learning approaches (i.e., systematic learning progression) into online site visits to facilitate students’ development of situated knowledge. In this project, a collaborative online site visit focused on building mechanical systems was created, where students worked in pairs to achieve four specific learning objectives, progressing from conceptual to procedural knowledge regarding building mechanical systems. The findings provide insights into the integration of systematic learning progression within virtual collaborative spaces for online site visits and demonstrate the effectiveness of such site visits in supporting students’ situated knowledge. 

Abstract Increasing the albedo of urban surfaces, through strategies like white roof installations, has emerged as a promising approach for urban climate adaptation. Yet, modeling these strategies on a large scale is limited by the use of static urban surface albedo representations in the Earth system models. In this study, we developed a new transient urban surface albedo scheme in the Community Earth System Model and evaluated evolving adaptation strategies under varying urban surface albedo configurations. Our simulations model a gradual increase in the urban surface albedo of roofs, impervious roads, and walls from 2015 to 2099 under the SSP3‐7.0 scenario. Results highlight the cooling effects of roof albedo modifications, which reduce the annual‐mean canopy urban heat island intensity from 0.8°C in 2015 to 0.2°C by 2099. Compared to high‐density and medium‐density urban areas, higher albedo configurations are more effective in cooling environments within tall building districts. Additionally, urban surface albedo changes lead to changes in building energy consumption, where high albedo results in more indoor heating usage in urban areas located beyond 30°N and 25°S. This scheme offers potential applications like simulating natural albedo variations across urban surfaces and enables the inclusion of other urban parameters, such as surface emissivity. 

As urban populations grow, cities are becoming more complex, driving the deployment of interconnected sensing systems to realize the vision of smart cities. These systems aim to improve safety, mobility, and quality of life through applications that integrate diverse sensors with real-time decision-making. Streetscape applications—focusing on challenges like pedestrian safety and adaptive traffic management—depend on managing distributed, heterogeneous sensor data, aligning information across time and space, and enabling real-time processing. These tasks are inherently complex and often difficult to scale. The Streetscape Application Services Stack (SASS) addresses these challenges with three core services: multimodal data synchronization, spatiotemporal data fusion, and distributed edge computing. By structuring these capabilities as clear, composable abstractions with clear semantics, SASS allows developers to scale streetscape applications efficiently while minimizing the complexity of multimodal integration. We evaluated SASS in two real-world testbed environments: a controlled parking lot and an urban intersection in a major U.S. city. These testbeds allowed us to test SASS under diverse conditions, demonstrating its practical applicability. The Multimodal Data Synchronization service reduced temporal misalignment errors by 88%, achieving synchronization accuracy within 50 milliseconds. Spatiotemporal Data Fusion service improved detection accuracy for pedestrians and vehicles by over 10%, leveraging multicamera integration. The Distributed Edge Computing service increased system throughput by more than an order of magnitude. Together, these results show how SASS provides the abstractions and performance needed to support real-time, scalable urban applications, bridging the gap between sensing infrastructure and actionable streetscape intelligence.