人与自然耦合系统氮通量计算域本体的构建与实现
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摘要
人类活动已经剧烈地改变了生态系统的氮生物地球化学循环过程,在增加系统生产力的同时,也带来了严重的环境和健康问题。随着人类活动干扰的越来越强,自然的生态系统结构与功能发生破缺,进而形成了农田、城市、牧场、工厂等功能系统,再进一步自组织升级为人与自然耦合系统(CHANS)。目前,全球经济飞速发展,环境氮污染严重,量化氮在系统中的流动格局,从而合理地利用氮素、在满足人类需要的同时降低其负面效应,成为人类在21世纪必须解决的科学挑战。
目前,大尺度生态系统氮通量的计算主要依靠半经验模型(Quasi-empirical Model),即在收集到的各类参数的基础上,利用经验公式来求解氮通量的大小。然而,在运用半经验模型的过程中遇到一些问题,其中包括：1)变量的缺失导致计算完备性无法保证；2)不确定性分析困难；3)数据无法规范共享。本体(ontology)是描述概念及概念间关系的语义模型,它可以统一和丰富对数据的描述从而促进数据的共享；而且,其推理机制和概念层次结构可以为半经验模型提供缺失变量下的自动推理与不确定性分析等功能。
为解决上述问题,本研究为氮通量半经验计算模型构建了域本体(nitrogen flux calculation ontology, NFCO),并提出了一个基于NFCO的自动推理和不确定性分析框架。NFCO及自动推理分析框架可以改善人与自然耦合系统氮通量的计算质量,为建立大尺度生态系统氮循环数据库提供了基础。
Human activities have intensively altered the nitrogen cycle of terrestrial ecosystems, increasing system productivity, but also bringing environmental and health problems. With the strengthening of human activity disturbances, the structure and function of natural ecosystems have been breaking, forming cropland, urban, pasture, industry and other functional systems, further self-organizing and upgrading to a coupled human and natural system (CHANS). Nowadays, as the rapid development of global economy, Nitrogen pollution is becoming more and more serious. So, quantifying Nitrogen flux in the system to utilize Nitrogen reasonably, satisfy human requirements as well as decrease negative effects turns to science challenges which must be solved in21st century for human beings.
At present, nitrogen flux calculation mainly depends on quasi-empirical models which quantify nitrogen fluxes using empirical formulas based on various kinds of collected parameters. However, quasi-empirical model has suffered from several limitations in its application, including:(1) completeness of calculation cannot be ensured due to the lacking of variables;(2) uncertainty analysis is difficult;(3) data sharing is lack of standardization. Ontology is a semantic model to describe concepts and their relations. It can unify and enrich the description of data to improve the sharing of data. In addition, the reasoning mechanism and hierarchy of ontology could provide automatic reasoning function for quasi-empirical models to find out unavailable variables and conduct uncertainty analysis.
This paper constructs a domain ontology for quasi-empirical models of nitrogen flux calculation (NFCO), and proposes a framework of automatic reasoning and uncertainty analysis based on NFCO. The NFCO and framework would improve the quality of CHANS nitrogen flux calculation, build the solid foundation for establishing CHANS nitrogen cycle database.
目前,大尺度生态系统氮通量的计算主要依靠半经验模型(Quasi-empirical Model),即在收集到的各类参数的基础上,利用经验公式来求解氮通量的大小。然而,在运用半经验模型的过程中遇到一些问题,其中包括：1)变量的缺失导致计算完备性无法保证；2)不确定性分析困难；3)数据无法规范共享。本体(ontology)是描述概念及概念间关系的语义模型,它可以统一和丰富对数据的描述从而促进数据的共享；而且,其推理机制和概念层次结构可以为半经验模型提供缺失变量下的自动推理与不确定性分析等功能。
为解决上述问题,本研究为氮通量半经验计算模型构建了域本体(nitrogen flux calculation ontology, NFCO),并提出了一个基于NFCO的自动推理和不确定性分析框架。NFCO及自动推理分析框架可以改善人与自然耦合系统氮通量的计算质量,为建立大尺度生态系统氮循环数据库提供了基础。
Human activities have intensively altered the nitrogen cycle of terrestrial ecosystems, increasing system productivity, but also bringing environmental and health problems. With the strengthening of human activity disturbances, the structure and function of natural ecosystems have been breaking, forming cropland, urban, pasture, industry and other functional systems, further self-organizing and upgrading to a coupled human and natural system (CHANS). Nowadays, as the rapid development of global economy, Nitrogen pollution is becoming more and more serious. So, quantifying Nitrogen flux in the system to utilize Nitrogen reasonably, satisfy human requirements as well as decrease negative effects turns to science challenges which must be solved in21st century for human beings.
At present, nitrogen flux calculation mainly depends on quasi-empirical models which quantify nitrogen fluxes using empirical formulas based on various kinds of collected parameters. However, quasi-empirical model has suffered from several limitations in its application, including:(1) completeness of calculation cannot be ensured due to the lacking of variables;(2) uncertainty analysis is difficult;(3) data sharing is lack of standardization. Ontology is a semantic model to describe concepts and their relations. It can unify and enrich the description of data to improve the sharing of data. In addition, the reasoning mechanism and hierarchy of ontology could provide automatic reasoning function for quasi-empirical models to find out unavailable variables and conduct uncertainty analysis.
This paper constructs a domain ontology for quasi-empirical models of nitrogen flux calculation (NFCO), and proposes a framework of automatic reasoning and uncertainty analysis based on NFCO. The NFCO and framework would improve the quality of CHANS nitrogen flux calculation, build the solid foundation for establishing CHANS nitrogen cycle database.
引文
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21. Gu BJ, Chang J, Ge Y, et al.2009. Anthropogenic modification of the nitrogen cycling within the Greater Hangzhou Area system, China. Ecological Applications, 19:974-988.
22. Hsieh SH, Lin HT, Chi NW, et al.2011. Enabling the development of base domain ontology through extraction of knowledge from engineering domain handbooks. Advanced Engineering Informatics,25:288-296.
23. Howarth RW.2005. The development of policy approaches for reducing nitrogen pollution to coastal waters of the USA. Science in China Series C-Life Sciences,48: 791-806.
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26. Jones JA.2012. Ecosystem processes and human influences regulate streamflow response to climate change at long-term ecological research sites. BioScience,62: 390-404.
27. Kaye JP, Groffman PM, Grimm NB, et al.2006. A distinct urban biogeochemistry? Trends in Ecology and Evolution,21:192-199.
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