ITR: Grid Computing for Ecological Modeling and Spatial Control

ITR：用于生态建模和空间控制的网格计算

• 批准号: 0427471
• 负责人: Louis Gross
• 金额: $ 141.66万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0427471&HistoricalAwards=false
• 关键词: ITR; Grid; Computing; Ecological; Modeling

Award AbstractEnvironmental problems related to natural resource management span a wide variety of spatial, temporal and biotic hierarchy levels. Resource managers are charged with local, short-term decisions regarding controlling access and types of use for sub-areas within larger natural areas, as well as much longer-term planning for entire areas as large as many thousands of hectares. Similarly, regional-scale planning for water flows, hunting regulations, preserve allocation, and forest harvesting requires stakeholders to provide input to the process, and such planning has led to numerous contentious public debates throughout the US. The main objective of this project is the development of computational tools, utilizing grid-computing, to assist natural resource managers in assessing the impacts of alternative management plans. The central theme of this proposal is that evaluating the impacts of human actions to manage natural systems requires the use of computational models utilizing the best available science to analyze potential effects. To be effective, such models must be defensible scientifically, readily available to various stakeholders and extensible to allow new users to evaluate alternative plans, assumptions and choices of criteria to prioritize management actions. This requires the use of computational ecology to develop models, visualize these models, consider alternative human controls within these models and analyze from an optimization perspective the various controls, based upon social choice criteria that may vary from stakeholder to stakeholder.Due to the variety of scales involved in natural resource management, the use of a multimodelingapproach is appropriate. In this, different models with potentially different mathematical andcomputational forms are chosen for different components of the system, based upon the necessary levels of detail and available data for different components. These models are linked into a multimodel to evaluate the interactions of biotic and abiotic components. Grid computing provides a natural framework to develop toolsets for ecological multimodels due to the dispersed nature of datasets, software and computational resources, in addition to the general lack of appropriate hardware at many natural resource agencies. The challenges go well beyond the current state-of-the-art in geographic information systems, requiring spatially-explicit dynamic models linked to spatio/temporal optimization schemes. Courses for managers and the engagement of underrepresented groups are planned.

与自然资源管理有关的环境问题跨越了各种各样的空间、时间和生物层次。资源管理人员负责就控制较大自然区域内的次区域的准入和使用类型作出当地的短期决定，并负责对多达数千公顷的整个区域进行长期规划。类似地，有关水流、狩猎法规、保护区分配和森林采伐的区域规模规划需要利益相关者为这一过程提供投入，这种规划在美国各地引发了许多有争议的公众辩论。该项目的主要目标是利用网格计算开发计算工具，以协助自然资源管理人员评估备选管理计划的影响。该提案的中心主题是，评估人类管理自然系统的行动的影响需要使用计算模型，利用现有的最佳科学来分析潜在的影响。为了有效，这种模式必须在科学上是合理的，随时可供各种利益攸关方使用，并可扩展，使新用户能够评估替代计划、假设和标准选择，以确定管理行动的优先次序。这需要使用计算生态学来开发模型，可视化这些模型，考虑这些模型中的替代人类控制，并从优化的角度分析各种控制，基于可能因利益相关者而异的社会选择标准。在这种情况下，根据不同组件的必要详细程度和可用数据，为系统的不同组件选择具有潜在不同数学和计算形式的不同模型。这些模型连接成一个多模型，以评估生物和非生物成分的相互作用。由于数据集、软件和计算资源的分散性，以及许多自然资源机构普遍缺乏适当的硬件，网格计算为开发生态多模型工具集提供了一个自然的框架。这些挑战远远超出了当前最先进的地理信息系统，需要空间显式动态模型链接到空间/时间优化方案。 计划为管理人员开设课程，并让任职人数不足的群体参与。