Concerning the ever-changing wetland environment, the efficient extraction of wetland information holds great significance for the research and management of wetland ecosystems. China’s vast coastal wetlands possess rich and diverse geographical features. This study employs the SegFormer model and Sentinel-2 data to conduct a wetland classification study for coastal wetlands in Yancheng, Jiangsu, China. After preprocessing the Sentinel data, nine classification objects (construction land, Spartina alterniflora (S. alterniflora), Suaeda salsa (S. salsa), Phragmites australis (P. australis), farmland, river system, aquaculture and tidal falt) were identified based on the previous literature and remote sensing images. Moreover, mAcc, mIoU, aAcc, Precision, Recall and F-1 score were chosen as evaluation indicators. This study explores the potential and effectiveness of multiple methods, including data image processing, machine learning and deep learning. The results indicate that SegFormer is the best model for wetland classification, efficiently and accurately extracting small-scale features. With mIoU (0.81), mAcc (0.87), aAcc (0.94), mPrecision (0.901), mRecall (0.876) and mFscore (0.887) higher than other models. In the face of unbalanced wetland categories, combining CrossEntropyLoss and FocalLoss in the loss function can improve several indicators of difficult cases to be segmented, enhancing the classification accuracy and generalization ability of the model. Finally, the category scale pie chart of Yancheng Binhai wetlands was plotted. In conclusion, this study achieves an effective segmentation of Yancheng coastal wetlands based on the semantic segmentation method of deep learning, providing technical support and reference value for subsequent research on wetland values.

The present study used bibliometric methods to analyze the literature regarding the biochar effects on soil that are included in the Web of Science Core Collection database and quantified the annual number of publications in the field and distribution of publications. Using CiteSpace as a visual analytic software for the literature, the distribution of the subject categories, author collaborations, institution collaborations, international (regional) collaborations, and cocitation and keyword clustering were analyzed. The results showed the basic characteristics of the literature related to the effects of biochar on soil. Furthermore, the main research powers in this field were identified. Then, we recognized the main intellectual base in the domain of biochar effects on soil. Meanwhile, this paper revealed the research hotspots and trends of this field. Furthermore, focuses of future research in this field are discussed. The present study quantitatively and objectively describes the research status and trends of biochar effects on soil from the bibliometric perspective to promote in-depth research in this field and provide reference information for scholars in the relevant fields to refine their research directions, address specific scientific issues, and help scholars to seek/establish relevant collaborations in their fields of interests.

The migration of nitrogen (N) from farmland to lake aggravates eutrophication. Riparian buffer strips (RBSs) are crucial in alleviating nitrogen into water bodies. This study examined the impacts of different RBS patterns on nitrogen removal. The effects of different RBSs of various widths (5, 15, 30, and 40 m), with different vegetation types (Taxodium hybrid ‘Zhongshanshan’, poplar (Nanlin-95), and a mixed forest of T. hybrid ‘Zhongshanshan’ and poplar) and at different densities (400, 1,000, and 1,600 plants·hm−2) on the TN, NH4+-N and NO3−-N removal rates in different depths of runoff water were studied. The results showed that the 15 m-wide RBS removed nitrogen the most effectively, with average removal rates of NH4+-N, NO3−-N and TN reaching 67.79%, 65.93% and 65.08%, respectively. Among the RBSs with different vegetation types, the poplar forest RBS removed the most NH4+-N (74.28%) and NO3−-N (61.71%). The mixed-forest RBS removed the most TN (65.57%). The RBS with 1,000 plants·hm−2 was more suitable in terms of the removal of NH4+-N (74.25%), NO3−-N (71.08%) and TN (62.67%). The conclusion can provide the basis of vegetation and width optimization for the design and construction of an RBS for maximum eutrophication nutrient removal.

Extensive nutrient leaching has been a major concern in the establishing stage of green roofs. Although an addition of biochar to the green roof substrates has been increasingly recommended, the extent to which this addition can affect the runoff quality is still largely unknown. Using biochars made from maize straws (MSB) and rice husks (RHB), this study investigated the effects of biochar addition rates (0%, 10%, 15%, and 20% biochar, v/v) on the runoff quality of new green roofs over 6 months. Our results show that the addition of biochar significantly affected the runoff quality. With an increasing biochar addition rate (10∼20%), the mean total nitrogen (TN) concentration in the runoff decreased from 103.68 mg L${}^{-1}$ (CK) to 26.21∼52.77 mg L${}^{-1}$ (RHB) and 10.12∼3.97 mg L${}^{-1}$ (MSB), the mean dissolved organic carbon (DOC) concentration decreased from 94.47 mg L${}^{-1}$ (CK) to 101.76∼59.41 mg L${}^{-1}$ (RHB) and 52.45∼26.73 mg L${}^{-1}$ (MSB), and the mean pH increased from 7.15 (CK) to 7.42∼7.50 (RHB) and 7.49∼7.71 (MSB). However, the mean total phosphorus (TP) concentration increased from 0.27 mg L${}^{-1}$ (CK) to 0.22∼0.57 mg L${}^{-1}$ (RHB) and 0.58∼1.07 mg L${}^{-1}$ (MSB). Generally, the N and DOC concentrations were lower in the treatment with added MSB than RHB, but the P concentrations and pH were higher. The N concentration was significantly negatively correlated with the single rainfall and cumulative rainfall in the CK- and RHB-added treatments but not in the MSB-added treatments, suggesting that the addition of MSB affected the process of N leaching from the substrate. Overall, we recommend adding 10% maize straw biochar to the green roof substrate to reduce the initial nutrient leaching from the new green roof and improve the runoff water quality.

Magnetite/zirconium-comodified attapulgite (Fe/ZrATP) acting as a novel phosphorus (P) sorbent was synthesized, characterized and applied to control P in an aquatic environment. Batch experiments demonstrated that at an adsorption dose of 0.2 g, 97.8% of the phosphate was rapidly sequestered from aqueous solution within 24 h, and the composite reached a maximal sorption capacity of 3 mg/g. The adsorption performance of the adsorbent Fe/ZrATP was minimally affected by changes in the initial pH (pH = 2–11). In addition, Fe/ZrATP presented excellent selectivity for phosphate when coexisting ions that often occur in water bodies were present; the solution ionic strength exerted little influence on phosphate sorption behavior. Adsorption and desorption experiments indicated that the removal of phosphate was mainly due to adsorption. The Fe/ZrATP adsorption isotherm was fitted to the Freundlich adsorption model. Moreover, the composite demonstrated excellent recyclability performance. The P adsorption mechanism of Fe/ZrATP involves electrostatic interactions, ligand exchange and surface precipitation. Our findings indicated that the separable Fe/ZrATP demonstrated high efficiency and sustainable phosphate removal, which is promising in phosphate removal and recovery applications

The grazing activity of animals has a significant role on the environmental modification of land. In the coastal wetlands of eastern China, long-term David deer (Elaphurus davidianus) grazing has caused the degradation of various ecological elements in the area. Still, few studies have been reported concerning the effects of David deer grazing on the soil microorganisms of their habitats. We analyzed the community structure of soil bacteria and fungi in an area of continuous annual grazing and another area without traces of David deer grazing so as to learn about the effects of deer grazing on the soil microbial community structure in a spatial instead of temporal way, in preparation for improving the environment for deer survival. David deer grazing drastically changed the physicochemical characteristics of the soil, accelerating the alkalinization process and inhibiting the buildup of nutrients. There were differences in the microbial community structure between the grazed and the control areas, with bacteria predominating. The control had a higher level of bacterial and fungal alpha-diversity than the grazed area. The makeup of the soil’s microbial community was also influenced, except for the dominant microbial at the phylum level. In addition to the establishment of numerous complex fungal functional types, David deer grazing increased the number of bacterial functional types linked to the carbon cycle. The impacts of soil pH and urease activity on bacterial and fungi populations were highlighted using the redundancy analysis. This study demonstrates that David deer grazing changes and complicates microbial functional kinds of composition, as well as modifies the composition of the soil’s microbial community, improving the soil nutrient cycling process, mainly the carbon element.