. "Web-Based Ecological Decision Support System." Agricultural Water Management: Proceedings of a Workshop in Tunisia (Series: Strengthening Science-Based Decision Making in Developing Countries). Washington, DC: The National Academies Press, 2007.
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Agricultural Water Management: Proceedings of a Workshop in Tunisia
media in managing and delivering information in the current electronic age, Wagner (2003) showed that the use of traditional desktop databases and CD-ROMs has been in decline during the past decades, while the use of World Wide Web (WWW) internet interfaced data collection and retrieval has seen exponential and continues to grow. The most common form of organizing and delivering spatial data using WWW is the linkage of a Web-based Geographical Information System (Web-GIS) and a backend relational database. Users with a web browser, can view, query, and manipulate the presented dataset to create a new dataset, or to access more information through a geo-referenced query delivered through the Web-GIS interface to the backend database. The Web-GIS mediated data retrieval and data organization greatly improved the usability of scientific data and research findings by decision-makers. The advantage of Web-GIS data portal is that it gives structure to the otherwise disaggregated collection of data and facts. In addition to the basic on-line GIS functions of search and overlay, it also provides statistical summaries and administrative functions. Web-GIS is seen as a way for promoting grassroots monitoring, data collection, and public involvement in environmental management. One example of such use of a web-based mapping program in river health monitoring and management is described by Graham et al. (2004). All stakeholders in the catchment of interest were provided with the opportunity to be involved in water sampling and data input into a web-based mapping and scoring system that calculates key indicators for pollution and can be used by management personnel for improved environmental management.
Natural resources and their management are intrinsically complex due to the dynamic balance and interactions among coexisting biotic agents and their abiotic environments within an ecosystem. Computer models have long been used for research on complex ecosystems, forming the basis for an integrated, system approach to management planning and implementation guidance. In an essay that discusses the future generation of ecological models for the purpose of environmental protection in natural resources management, Linthurst et al. (1999) outlined the direction of more advanced future modeling system developed in the form of a must-have list. The focus of the discussion was on modeling-mediated, watershed water quality control. The overall recommendations, which followed the ecological modeling research within the EPA’s Office of Research and Development (ORD), were for: (1) a common software framework for ecological modeling to improve model(s) usability to aid in making management decisions and (2) further develop and improve watershed-scale (multi-scale) modeling to address more realistically the fate of multiple pollutants in multiple environmental media. For individual model improvement, the vision calls for the development of (1) “State-of-the-science process algorithms and component computational models with flexible scaling to provide problem-solving methodologies that are applicable at multiple geographic and temporal scales”; (2) “State-of-the-science atmospheric, terrestrial, aquatic, and biotic process models and stressors and effects models that predict real-world conditions and their incorporation into a common framework; (3) “Improved ability to interconnect one system with another system (e.g., the atmosphere and surface water ecosystems) and exchange information in between;” and (4) the linkage of ecological models to geographic information system (GIS) technology. To a large degree, the current generation of ecological models has become much more sophisticated than their predecessors in terms of dealing with coexisting biological species or pollutant agents and representation of underlying processes in hydrology, soil erosion, and nutrient cycling. However, dynamic temporal and spatial scaling of individual models is still a largely unaddressed issue. Yet, from the recommendations listed above, it is obvious that a collection of specialized models