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13. Effects of crabs on greenhouse gas emissions, soil nutrients, and stoichiometry in a subtropical estuarine wetland 260 __

Author

Chen, Xiaoxuan, Wiesmeier, Martin, Sardans i Galobart, Jordi, Van Zwieten, Lukas, Fang, Yunying, Gargallo-Garriga, Albert, Chen, Youyang, Chen, Shuyun, Zeng, Congsheng, Peñuelas, Josep, and Wang, Weiqi

Subjects
Elemental stoichiometry, Nitrogen, Wetlands, Phosphorus, Greenhouse gas emission, Carbon
Abstract

Crabs may elicit effects on wetland carbon (C), nitrogen (N), and phosphorus (P) concentrations and associated ecological stoichiometry. In this study, we assessed effects of crabs on carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions; soil C, N, and P concentrations; and stoichiometry in upper and mid-tidal flats of an estuarine wetland in China. The results showed that averaged CO2, CH4, and N2O fluxes were greater in the upper and mid-tidal flats in the presence of crabs, being 46.4, 66.7, and 69.7% and 53.6, 143, and 73.1% greater than control, respectively. Mixed model analyses showed overall positive relationships between wetland soil CO2 CH4 and N2O emissions (F = 4.65, P = 0.033; F = 42.42, P = 0.042 and F = 10.2, P = 0.0018, respectively) in the presence of crabs, taking into account season, flooding intensity, and plot effects. This may be related to the direct effects of respiration and the indirect effects of feeding, excretion, and disturbance of soil on microorganisms and/or plant roots. There were no effects of crabs on total C or N concentrations, whereas decreased soil total P concentrations, especially in the upper-tidal flats (P = 0.04). Crab presence was positively associated with soil C/P and N/P ratios (P

Published
2020

18. A New Framework for Traffic Anomaly Detection

Author

Lan, Jinsong, Long, Cheng, Wong, Raymond Chi Wing, Chen, Youyang, Fu, Yanjie, Guo, Danhuai, Liu, Shuguang, Ge, Yong, Zhou, Yuanchun, Li, Jianhui, Lan, Jinsong, Long, Cheng, Wong, Raymond Chi Wing, Chen, Youyang, Fu, Yanjie, Guo, Danhuai, Liu, Shuguang, Ge, Yong, Zhou, Yuanchun, and Li, Jianhui

Abstract

Trajectory data is becoming more and more popular nowadays and extensive studies have been conducted on trajectory data. One important research direction about trajectory data is the anomaly detection which is to find all anomalies based on trajectory patterns in a road network. In this paper, we introduce a road segment-based anomaly detection problem, which is to detect the abnormal road segments each of which has its “real” traffic deviating from its “expected” traffic and to infer the major causes of anomalies on the road network. First, a deviation-based method is proposed to quantify the anomaly of reach road segment. Second, based on the observation that one anomaly from a road segment can trigger other anomalies from the road segments nearby, a diffusion-based method based on a heat diffusion model is proposed to infer the major causes of anomalies on the whole road network. To validate our methods, we conduct intensive experiments on a large real-world GPS dataset of about 23,000 taxis in Shenzhen, China to demonstrate the performance of our algorithms.

Published
2014

19. A New Framework for Traffic Anomaly Detection

Author

Lan, Jinsong, primary, Long, Cheng, additional, Wong, Raymond Chi-Wing, additional, Chen, Youyang, additional, Fu, Yanjie, additional, Guo, Danhuai, additional, Liu, Shuguang, additional, Ge, Yong, additional, Zhou, Yuanchun, additional, and Li, Jianhui, additional

Published
2014
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