Science Bulletin最新文献

The worsening water-food-energy nexus presents a critical challenge for sustainable development. Simultaneously extracting freshwater and boron from seawater or brine with minimal energy input offers a promising yet underexplored strategy to address these interconnected issues. Herein, we propose a solar-driven multi-field synergistic strategy that rationally integrates temperature, concentration, and flowing fields to co-harvest freshwater and boron resources. For conceptual demonstration, we fabricated a (MXene-MgO)@sodium alginate (SA) composite gel (i.e., MMS) by co-doping MgO (a boron adsorbent) and MXene (a dual-functional material acting as both photothermal converter and boron adsorption aid) into an SA matrix. Under 1 sun illumination, the developed MMS demonstrated a high evaporation rate of 2.14 kg m^-2 h^-1 and a boron adsorption capacity of 225.52 mg m^-2 within 9 h. Outdoor field tests further well validated its practical viability, yielding 5.20 kg m^-2 of freshwater and recovering 122.45 mg m^-2 of boron daily. Most notably, the recovered boron could remarkably enhance agricultural productivity, increasing the seed germination rate by 13% and tripling biomass production relative to the boron-deficient control. Overall, this work establishes a revolutionary paradigm within the water-food-energy nexus, particularly relevant for resource-scarce coastal regions.

We present an observational confirmation of Hawking's black-hole area theorem using the newly released gravitational-wave data from the GWTC-4.0. We analyze the high signal-to-noise ratio binary black hole merger GW230814 and measure the (total) horizon area of the black holes before and after the merger. For preferred (and reasonable) choices of the post-truncation start time, the horizon area of the remnant black hole is found to be greater than the total horizon area of the two pre-merger black holes at a high possibility (at least ≳99.5%). Importantly, our analysis accounts for sky-location uncertainty. These results provide a stringent observational confirmation of the black-hole area law, further bolstering the validity of classical general relativity in the dynamical, strong-field regime.

While existing early-warning systems struggle to achieve cross-species cyanobacterial risk prediction with the required synchronicity and accuracy in aquatic ecosystems, our study pioneers a genome architecture-driven monitoring paradigm through decoding 317 cyanobacterial metagenome-assembled genomes from the world's largest phosphorus-limiting water transfer system, the Middle Route of the South-to-North Water Diversion Canal (MR-SNWDC). We found an evolutionary blueprint where genome minimization (<3 Mbp) confers ecological dominance under phosphorus scarcity. These streamlined genomes showed predominance and remarkable seasonal dynamics and demonstrated metabolic specialization in phosphorus turnover, light harvesting, and carbon fixation compared to larger genomes. Importantly, we identified a 3 Mbp genomic threshold distinguishing low-risk cyanobacterial consortia from their toxin-producing counterparts. This genome-proxy system enables preemptive risk mitigation by predicting toxic transitions through genome size tracking, fundamentally advancing algal management from reactive monitoring to proactive regulation in water transfer networks.

Soil moisture is critical for climate prediction, ecological management, and disaster warning. However, multi-source datasets show spatiotemporal inconsistencies and uncertain regional applicability due to algorithmic and observational limitations. We assess the statistical performance and spatiotemporal variations of 23 global surface soil moisture datasets (1980-2023) from reanalysis, land surface models, and microwave remote sensing across global and regional scales (classified by Köppen climates and IPCC land uses). Results show a slight long-term (1980-2023) global surface soil moisture decline (-4.30 × 10^-4 m³ m^-3 a^-1), with some datasets indicating short-term wetting (7.17 × 10^-4 m³ m^-3 a^-1) post-2010 (2010-2023). A dual-validation against 992 and a filtered subset of 483 highly representative in situ stations shows that most products perform moderately well (Pearson R ≈ 0.5-0.7). Microwave remote sensing products, especially those based on SMAP, consistently demonstrate superior performance in capturing temporal dynamics (R ≈ 0.7). Our analysis demonstrates that spatial representativeness error can mask true performance, with validation in the tropics improving dramatically after site filtering (mean R increase of 0.41). The findings highlight product-specific strengths and weaknesses, underscoring the necessity of a science-informed, application-specific approach to dataset selection for robust hydrological and climatic research.