It is an important branch of erosion research to control soil erosion on eroded gullies and slopes by using vegetation filter strip. Several simulated rainfall experiments were carried out in soil tanks filled with loess sandy loam taken from a typical eroded gully area with less vegetation coverage in Yanghe hilly basin in Xuanhua District, Zhangjiakou City, Hebei Province. The soil and water conservation effects of two different vegetation setting modes were compared under the same vegetation strip width and different rainfall intensities and slopes. During the rainfall process, the changes of runoff and sediment yield and nutrient loss were not stable, but the same erosion index had similar variation trends under different combinations of rainfall intensity, slope and vegetation coverage. Multiple regression results showed that runoff and sediment production in eroded gully can be effectively reduced through vegetation filter strips, which are jointly affected by rainfall intensity and slope. There was no significant difference in the amount of runoff and sediment yield between the two vegetation setting modes. Rainfall intensity and slope gradient showed different strengths of impact on nutrient loss. Through cluster analysis, the results showed that the impacts of rainfall intensity, slope gradient and vegetation setting modes on soil and water loss on slope can be equal or offset. In general, setting vegetation filter strips can offset the effects of rainfall intensity and slope, but vegetation regulation of erosion was not obvious under extreme rainfall and steep slope conditions. What’s more, rainfall intensity had a dominant effect on erosion. The results in this research may provide reference for practical application of vegetation filter strips on eroded slopes.

A series of polyimides (PIs) with good heat sealability were synthesized from an asymmetric aromatic dianhydride, 2,3,3′,4′-oxydiphthalic anhydride, and aromatic ether diamines with different structures featured by ether amounts, substituted positions of ether linkages, and substituted positions of amino groups. In detail, the effects of these three substructures in the diamine were investigated on thermal resistance, thermoplasticity, and heat sealability of the PI film. It is found that the glass transition temperatures and heat-sealing strengths of the prepared PI films are influenced to different extents by the variations of the substructures, because of their different contributions to the chain mobility. These PI films are demonstrated to possess good heat sealability evidenced by completely fused heat-sealing interfaces and high heat-sealing strengths up to 580 N m⁻¹.

The research on regular and irregular vegetation pattern formation in semiarid regions is an important field in ecology. Applying the framework of coupled map lattice, a novel nonlinear space- and time-discrete model is developed based on discretizing the classical Klausmeier model and the vegetation pattern formation in semiarid regions is restudied in this research. Through analysis of Turing-type instability for the discrete model, the conditions for vegetation pattern formation are determined. The discrete model is verified by Klausmeier’s results with the same parametric data, and shows advantages in quantitatively describing diverse vegetation patterns in semiarid regions, such as the patterns of regular mosaicirregular patches, stripes, fractured stripesspots, and stripes-spots, in comparing with former theoretical models. Moreover, the discrete model predicts variations of rainfall and vegetation types can cause transitions of vegetation patterns. This research demonstrates that the nonlinear mechanism of the discrete model better captures the diversity and complexity of vegetation pattern formation in semiarid regions.

The topic of utilizing coupled map lattice to investigate complex spatiotemporal dynamics has attracted a lot of interest. For exploring the spatiotemporal complexity of a predator‐prey system with migration and diffusion, a new three‐chain coupled map lattice model is developed in this research. Based on Turing instability analysis, pattern formation conditions for the predator‐prey system are derived. Via numerical simulation, rich Turing patterns are found with subtle self‐organized structures under diffusion‐driven and migration‐driven mechanisms. With the variation of migration rates, the predator‐prey system exhibits a gradual dynamical transition from diffusion‐driven patterns to migration‐driven patterns. Moreover, new results, the self‐organization of non‐Turing patterns, are also revealed. We find that even in the cases where the nonspatial predator‐prey system reaches collapse, the migration can still drive pattern self‐organization. These non‐Turing patterns suggest many new possible ways for the coexistence of predator and prey in space, under the effects of migration and diffusion.

Soil nitrogen (N) mineralization typically governs the availability and movement of soil N. Understanding how factors, especially functional genes, affect N transformations is essential for the protection and restoration of forest ecosystems. To uncover the underlying mechanisms driving soil N mineralization, this study investigated the effects of edaphic environments, substrates, and soil microbial assemblages on net soil N mineralization in boreal forests. Field studies were conducted in five representative forests: Larix principis-rupprechtii forest (LF), Betula platyphylla forest (BF), mixed forest of Larix principis-rupprechtii and Betula platyphylla (MF), Picea asperata forest (SF), and Pinus sylvestris var. mongolica forest (MPF). Results showed that soil N mineralization rates (R_min) differed significantly among forests, with the highest rate in BF (p < 0.05). Soil properties and microbial assemblages accounted for over 50% of the variability in N mineralization. This study indicated that soil environmental factors influenced N mineralization through their regulatory impact on microbial assemblages. Compared with microbial community assemblages (α-diversity, Shannon and Richness), functional genes assemblages were the most important indexes to regulate N mineralization. It was thus determined that microbial functional genes controlled N mineralization in boreal forests. This study clarified the mechanisms of N mineralization and provided a mechanistic understanding to enhance biogeochemical models for forecasting soil N availability, alongside aiding species diversity conservation and fragile ecosystem revitalization in boreal forests.

Nitrogen (N) is a vital mineral nutrient for plant growth and occupies a pivotal position in biogeochemical systems. Soil nitrogen mineralization (SNM) in forests represents a significant limiting factor in terrestrial ecosystem productivity in the context of global climate change. To understand the research status and development trends of SNM in forests, 3576 articles spanning 2004 to 2024 from the Web of Science (WOS) database were analyzed using CiteSpace software. The results indicated that (1) the mean number of articles published in the recent ten-year period is 193, marking an approximate 17.8% increase compared to the preceding ten-year period (2004–2013), highlighting the continuous development of SNM research; (2) among the sampled articles, Soil Biology and Biochemistry, Forest Ecology and Management, Plant and Soil, and Biogeochemistry emerged as leading international journals that played a key role in shaping the development of the field and laid a solid foundation for future research efforts; (3) the USA and China emerged as the most productive countries in this field, with the Chinese Academy of Sciences standing out as a prominent institution at the forefront of this research domain; and (4) recent research is focusing on understanding the interactions between microbial communities and the environment during SNM. In summary, this study offers valuable insights into the research status and development trends of SNM in forests. It underscores the importance of ongoing interdisciplinary collaboration and innovation to further enhance our understanding of key ecological processes. Future research on SNM in forests is encouraged to delve deeper into its associations with forest productivity, carbon cycling, microbial functions, and global change. Additionally, exploring sustainable land management and process optimization is recommended to promote the healthy and sustainable development of forest ecosystems.