Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents’ quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development.

Knowledge of the responses of soil nitrogen (N) availability, fine root mass, production and turnover rates to atmospheric N deposition is crucial for understanding fine root dynamics and functioning in forest ecosystems. Fine root biomass and necromass, production and turnover rates, and soil nitrate-N and ammonium-N in relation to N fertilization (50 kg N ha−1 year−1) were investigated in a temperate forest over the growing season of 2010, using sequential soil cores and ingrowth cores methods. N fertilization increased soil nitrate-N by 16% (P<0.001) and ammonium-N by 6% (P<0.01) compared to control plots. Fine root biomass and necromass in 0–20 cm soil were 13% (4.61 vs. 5.23 Mg ha−1, P<0.001) and 34% (1.39 vs. 1.86 Mg ha−1, P<0.001) less in N fertilization plots than those in control plots. The fine root mass was significantly negatively correlated with soil N availability and nitrate-N contents, especially in 0–10 cm soil layer. Both fine root production and turnover rates increased with N fertilization, indicating a rapid underground carbon cycling in environment with high nitrogen levels. Although high N supply has been widely recognized to promote aboveground growth rates, the present study suggests that high levels of nitrogen supply may reduce the pool size of the underground carbon. Hence, we conclude that high levels of atmospheric N deposition will stimulate the belowground carbon cycling, leading to changes in the carbon balance between aboveground and underground storage. The implications of the present study suggest that carbon model and prediction need to take the effects of nitrogen deposition on underground system into account.

Marine aquaculture plays an important role in seafood supplement, economic development, and coastal ecosystem service provision. The precise delineation of marine aquaculture areas from high spatial resolution (HSR) imagery is vital for the sustainable development and management of coastal marine resources. However, various sizes and detailed structures of marine objects make it difficult for accurate mapping from HSR images by using conventional methods. Therefore, this study attempts to extract marine aquaculture areas by using an automatic labeling method based on the convolutional neural network (CNN), i.e., an end-to-end hierarchical cascade network (HCNet). Specifically, for marine objects of various sizes, we propose to improve the classification performance by utilizing multi-scale contextual information. Technically, based on the output of a CNN encoder, we employ atrous convolutions to capture multi-scale contextual information and aggregate them in a hierarchical cascade way. Meanwhile, for marine objects with detailed structures, we propose to refine the detailed information gradually by using a series of long-span connections with fine resolution features from the shallow layers. In addition, to decrease the semantic gaps between features in different levels, we propose to refine the feature space (i.e., channel and spatial dimensions) using an attention-based module. Experimental results show that our proposed HCNet can effectively identify and distinguish different kinds of marine aquaculture, with 98% of overall accuracy. It also achieves better classification performance compared with object-based support vector machine and state-of-the-art CNN-based methods, such as FCN-32s, U-Net, and DeeplabV2. Our developed method lays a solid foundation for the intelligent monitoring and management of coastal marine resources.

We studied nitrogen (N) resorption efficiencies (NRE), N use efficiencies (NUE), carbon-to-nitrogen ratios of green (C:Ngreen) and senesced (C:Nsenesced) foliage, and foliar litterfall for six tree species under three N treatments (control, no N addition; low N addition, 2.5 g N·m–2·year–1; and high N addition, 5.0 g N·m–2·year–1) in a mixed birch and poplar forest in northeastern China in 2007 and 2008. N additions were initiated in 2006. NRE, NUE, C:Ngreen, and C:Nsenesced were significantly decreased by N additions and tended to decrease with increasing N addition treatments. N additions significantly increased foliar litterfall of Acer mono Maxim., Betula platyphylla Sukatschev, Pinus koraiensis Siebold & Zucc., and Populus davidiana Dode and slightly altered litterfall of Fraxinus mandschurica Rupr. and Populus koreana Rehder. High N addition changed foliar litterfall of A. mono, F. mandschurica, P. davidiana, and P. koreana more than low N addition, whereas an opposite pattern was found for B. platyphylla and P. koraiensis. Our study showed that foliar litterfall responses to N additions varied among tree species, but this could not be predicted by the interspecific differences in NRE, NUE, C:Ngreen, and C:Nsenesced under each of the three N treatments.

SummaryObjective: This study was carried out to observe the enzymatic degradation of human dentin collagen fibrils exposed to exogenous collagenase in situ using atomic force microscopy, to understand the characteristics of the enzymatic degradation of collagen fibrils on dentin specimens. Methods: Polished dentin specimens from caries-free third molars were etched with citric acid, and then treated with an aqueous solution of 6.5% NaOCl for 120 s. The specimen was then put into a fluid cell and treated with a mixed solution of collagenase I (MMP-1) and collagenase II (MMP-8) for 9 h. AFM with contact mode was performed in situ to monitor the enzymatic degradation process of the dentin collagen fibrils. The distinctly topographic changes of the dentin surface were recorded continuously during different stages of the enzymatic degradation process. Results: The mixed solution of exogenous collagenase I and collagenase II could degrade dentin organic matrix (mainly collagen) efficiently, and the structures of dentin substrate were clearly exposed. Conclusion: It is possible to carry out real-time observations on the enzymatic biodegradation process of human dentin collagen fibrils on dentin specimens with atomic force microscopy in situ. By this means, the fine structures of the etched dentin substrate were clearly revealed, possibly contributing to the related study of human dentin in vitro.

Abstract:Although China has promoted the construction of Chinese Sustainable Ground Transportation (CSGT) to guide sustainable development, it may create substantial challenges, such as rapid urban growth and land limitations. This research assessed the effects of the Hangzhou Bay Bridge on impervious surface growth in Cixi County, Ningbo, Zhejiang Province, China. Changes in impervious surfaces were mapped based on Landsat images from 1995, 2002, and 2009 using a combination of multiple endmember spectral mixture analysis (MESMA) and landscape metrics. The results indicated that the area and density of impervious surfaces increased significantly during construction of the Hangzhou Bay Bridge (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009). Additionally, the bridge and connected road networks promoted urban development along major roads, resulting in compact growth patterns of impervious surfaces in urbanized regions. Moreover, the Hangzhou Bay Bridge promoted the expansion and densification of impervious surfaces in Hangzhou Bay District, which surrounds the bridge. The bridge also accelerated socioeconomic growth in the area, promoting rapid urban growth in Cixi County between 2002 and 2009. Overall, the Hangzhou Bay Bridge is an important driver of urban growth in Cixi County, and policy suggestions for sustainable urban growth should be adopted in the future.

& Key message During an N-deposition simulation experiment, we showed that low to medium addition of N had beneficial effects on growth and photosynthetic rates of Fraxinus mandshurica Rupr. seedlings, while beyond a threshold of 80 kg N ha −1 year −1 , performance plateaued and even declined at higher immissions. & Context Temperate forests are shifting from naturally N-limited toward N-saturated status with increasing N deposition. Yet, our knowledge regarding how seedling growth and physiology respond to excessive N input in temperate tree species remains very limited. & Aims The objective of this study was to examine growth and photosynthetic responses of F. mandshurica seedlings to a gradient of simulated N deposition. & Methods We conducted a 4-year study to investigate growth and photosynthetic responses of F. mandshurica seedlings to a large gradient of simulated N deposition (0, 20, 40, 60, 80, 100, and 120 kg N ha −1 year −1). Biomass accumulation and allocation, photosynthetic gas exchange, expression, and activities of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) in leaves were determined during the fourth growing season. Soil biochemical properties were measured to link them to the alterations in growth and photosynthetic traits across the N addition gradient. & Results Seedling growth and photosynthesis were dependent upon the rates of N deposition. The maximum rate of carboxylation (V c,max) and the net photosynthetic rate under saturating light (A sat) reached a maximum under 60 kg N ha −1 year −1. By contrast, highlevel N inputs (100 and 120 kg N ha −1 year −1) resulted in suboptimal values in biomass and photosynthetic activity. Nitrogen deposition also modulated the activity and expression of Rubisco in leaves with a maximum around 80-100 kg N ha −1 year −1. Redundancy analysis (RDA) showed that the changes of seedling growth and photosynthesis along the gradient of N deposition were mostly attributed to the variations of soil pH and total N content. & Conclusion Our data suggest that the threshold of N deposition is about 80 kg N ha −1 year −1 for F. mandshurica seedlings in this region. Excessive N input decreased performance on the seedling growth and photosynthesis.

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