BCC: Collaborative Research: Designing SKOPE: Synthesized Knowledge of Past Environments

科学研究的一个重要重点是了解人类社会与它们所依赖的气候、物理和生物环境之间的复杂相互作用，并反过来影响它们。当然，过去的环境往往与我们今天所经历的大不相同。此外，重要的社会和环境变化进程运行缓慢，有时只有在几十年或几个世纪后才能看到。为了研究近几十年来除短期以外的任何社会和自然过程，特定地点和时间的长期环境知识是必不可少的。不幸的是，关于过去环境的最新数据很难找到，甚至更难集成和解释。在金蒂格博士和他的同事们的指导下，该项目将为在线工具Skope(过去环境的综合知识)制定计划，该工具将提供关于人类在给定地点和时间体验的环境的最先进信息，无论是过去还是现在。利用明确的科学程序，它将对数据进行处理，以产生专门针对用户要求的环境信息的尖端综合。最初的开发计划是在美国西南部，但斯科普的设计将很容易扩展到其他地方和时间。一旦实施，Skope将可以在互联网上免费访问。它将适用于可持续发展、考古学、社会学、经济学、人类学、生态学以及资源管理和规划等领域。例如，它将直接受益于比较不同文明之间长期气候变化的社会后果的考古学家和研究生物多样性长期变化的生态学家。规划者可以利用其长期的环境重建来调查现有基础设施中的漏洞，这些漏洞不在历史记录提供的经验之外。学生和普通公众可以在他们学习、居住或参观的地方了解古代环境与现代环境的不同之处。Skope将访问现代和历史观测数据的在线数据库(例如，关于降雨量、温度和动植物分布的数据)以及过去环境指标的数据库(例如，根据树轮宽度重建的降雨量，以及在陈旧的考古遗址中发现的植物遗骸和动物骨骼)。解释不同类别数据的科学专家将制定程序，将这些不同的环境观测和指标转化为对感兴趣的时间和地点的环境的全面记录的科学综合。Skope的设计将以潜在用户在与学术、公共和私营部门专业人士举行的会议上陈述的需求为指导。该项目将确定关于当前和过去环境的主要数据来源，并将推广实现有用的综合所需的分析程序。随后的开发可以将该工具扩展到更多的地区和时间，并纳入更多类别的环境数据。

An important focus of scientific research is understanding the complex interactions between human societies and the climatic, physical, and biological environments on which they depend, and which they, in turn, influence. Past environments, of course, were often quite different from those we experience today. Furthermore, important processes of social and environmental change operate slowly and are sometimes visible only when viewed over decades or centuries. In order to study social and natural processes operating over anything other than short periods in recent decades, long-term environmental knowledge specific to particular locations and times is essential. Unfortunately, state-of-the-art data on past environments are difficult to find and even more difficult to integrate and interpret. Under the direction of Dr. Kintigh and his colleagues, the project will develop plans for an online tool, SKOPE (Synthesized Knowledge of Past Environments), that will provide state-of-the-art information about the environment experienced by humans at a given a place and time, past or present. Using explicit scientific procedures, it will process the data to yield a cutting-edge synthesis of environmental information specifically tailored to the user's request. Initial development is planned for the Southwest US, but SKOPE's design will be designed to be easily extended to other places and times. Once implemented, SKOPE will be freely accessible on the Internet. It will be applicable in such fields as sustainability, archaeology, sociology, economics, anthropology, and ecology as well as for resource management and planning. For example, it will directly benefit archaeologists comparing the social consequences of long-term climate change across different civilizations and ecologists investigating long-term changes in biodiversity. Planners could use its long-term environmental reconstructions to investigate vulnerabilities in existing infrastructure that are outside the experience provided by the historic record. Students and members of the general public could learn how ancient environments differed from contemporary ones in places they study, inhabit, or visit. SKOPE will access online databases of modern and historic observational data (for example, on rainfall, temperature, and plant and animal distributions) as well as databases of indicators for past environments (for example, rainfall reconstructed from tree-ring widths, and plant remains and animal bones found in dated archaeological sites). Scientific experts in the interpretation of different classes of data will develop procedures that transform these diverse environmental observations and indicators into a thoroughly documented scientific synthesis of the environment for the time and place of interest. The design of SKOPE will be guided by the needs stated by potential users in meetings with academic, public-, and private-sector professionals. The project will identify key sources of data on current and past environments and will generalize the analytical procedures required to achieve useful synthesis. Subsequent development could extend the tool to additional areas and times and incorporate more classes of environmental data.