Urban expansion, characterized by growing impervious surface area, severely disrupts wetland ecosystem functions and nutrient cycling processes. However, a holistic understanding of how urbanization affects wetland soil nitrogen cycling and the associated functional microorganisms remains unclear. In this study, the key soil nitrogen cycling processes and their associated core microbial functional genes across 22 wetlands were investigated along a rural–suburban–urban gradient. Results showed that soil total nitrogen and ammonium content in urban sites were significantly lower than those in rural sites. Although microbial alpha diversity did not change significantly, the E/O ratio (the abundance ratio of eutrophic to oligotrophic phyla) decreased sharply along the urbanization gradient. Metagenomic analysis revealed a systematic functional restructuring: urban wetlands exhibited upregulated genetic potential for nitrate scavenging and conservation (assimilatory and dissimilatory nitrate reduction to ammonium—ANRA/DNRA— and nitrate transport) but downregulated pathways for nitrogen acquisition (fixation) and organic matter processing. This shift indicates a microbial adaptation to nitrogen limitation in urban wetlands, where enhanced DNRA and ANRA pathways compete with nitrification and denitrification, crucially regulating nitrogen transformation rates. The study identifies soil organic carbon, pH, bulk density, and the interaction between key microbial taxa and nitrogen cycle gene groups as the primary factors controlling wetland soil nitrogen status under urban pressure. We conclude that urbanization threatens wetland nutrient functions not merely by habitat loss, but by inducing a functional microbial shift. These findings underscore the need for urban planning strategies that mitigate soil property changes to preserve the microbial basis of wetland ecosystem services.
Background: Al-based radiators are core components of offshore generator sets, and their anticorrosion performance directly affects the safe and stable operation and service life. Methods: A novel chitosan (CTS) derivative (CTS-ZIM) was synthesized through an amidation reaction by using a zwitterionic imidazole compound as a modifying monomer. Significant findings: CTS-ZIM shows a significantly enhanced inhibition performance, achieving an inhibition efficiency of 97.1% at a low concentration of 1000 mg L-1 for Al fin in a 1.0 M HCl solution. Weight loss method, electrochemical method, and physical characterizations demonstrate that the inhibitor effectively suppressed the corrosion process through adsorption on the steel surface. The introduction of the zwitterionic imidazole compound into CTS provides abundant ionic structures, unsaturated bonds (C--O, C--C, C--N), Schiff base moieties, imidazole rings, and heteroatoms (N, O). These changes enhance its adsorption on metal surfaces, favoring the formation of a protective layer. Moreover, density functional theory calculations indicate that the introduction of zwitterionic imidazole can enhance the adsorption strength and electron-donating ability of the inhibitor. It is believed that this work can provide sufficient guidance for the precise design of efficient corrosion inhibitors.
The core challenge in underwater object detection arises from the severe attenuation and blurring of spatial features caused by optical degradation in complex media. Existing attention mechanisms mainly rely on aggregating spatial intensities. However, this single-domain inductive bias struggles to distinguish high-intensity scattering noise from weak object signals. Furthermore, they lack an explicit mechanism to model global frequency-domain degradation patterns. To address these limitations, this paper proposes a physics-informed Spectral-Spatial Degradation-Aware Fusion Attention (SDFA) to enhance feature representation through cross-domain synergy. Specifically, SDFA uses a dual-stream architecture. In the spatial domain, local standard deviation decouples texture information from smooth backgrounds, suppressing caustic interference. In the frequency domain, Fourier analysis is utilized to explicitly model the spectral characteristics of medium degradation. An adaptive recalibration mechanism then suppresses noise while enhancing high-frequency semantic details attenuated by the water medium. Experimental results show that SDFA serves as a plug-and-play module, improving the accuracy and robustness of mainstream detectors on the DUO and RUOD benchmarks. These results demonstrate the effectiveness of joint spectral-spatial modeling in low signal-to-noise ratio environments. The source code of the proposed method is publicly available at https://github.com/djmnb/SDFA.
Extreme climate risks and farmland structural constraints are intensifying agricultural vulnerability, making the improvement of climate-smart agriculture (CSA) essential for enhancing agricultural resilience and sustain-ability. High-standard farmland construction (HSFC) represents an important practice for advancing CSA by improving cultivated land quality and farmland infrastructure. However, existing studies have mainly examined HSFC's effects on single outcomes, including yield, efficiency, or environmental performance, with insufficient attention to whether it can simultaneously advance multiple CSA objectives or generate synergies and trade-offs among them. To examine the multidimensional linkages between HSFC and CSA, this study proposes an integrated Pressure-State-Response-Objective (PSRO) analytical framework. Using 2003-2022 panel data for 122 counties in Hunan Province, we apply a continuous difference-in-differences (DID) model and mechanism tests to estimate HSFC's policy effects and assess transmission through input optimization, technology upgrading, and cultivated-land habitat quality. Results show that (1) HSFC has a positive and significant policy effect on CSA, with estimated coefficients of about 0.011-0.012 across specifications; (2) HSFC positively influences CSA in pillars food security and climate adaptation, but negatively affects pillar carbon mitigation in the short term; (3) heterogeneous effects are evident across regions, with stronger impacts where regional development conditions and land-consolidation potential are more favorable; (4) CSA gains from HSFC arise from improved farmland production conditions, reduced per-output input pressure, and complementary technological and cultivated-land habitat improvements. This study links a land-consolidation mega-program with a multi-pillar CSA index under an integrated PSRO framework and offers guidance for coordinating food security, climate resilience, and carbon mitigation.
