CyberSEES: Type 1: Fostering Non-Expert Creation of Sustainable Polycultures through Crowdsourced Data Synthesis

该项目整合了计算机和可持续发展科学的研究，目标是实现可持续粮食安全的新方法。pi建议将网络人类系统和众包研究与农业生态学相结合，其主要研究目标有两个：1)了解在线设计工具如何通过提高当地粮食生产来促进可持续性，2)利用植物物种数据库的种群作为可适应智能众包的一类问题的实例，并在众包优化方面开拓新知识。作为该项目的一部分，研究团队将设计、构建、部署和评估可持续多元文化作曲家（Sustainable Polyculture Composer），这是一个在线软件工具，用于帮助设计小型植物农业生态系统（例如后院食物林）。长期粮食安全是可持续性的核心。美国的食品供应链助长了全球变化，也容易受到其影响。面对全球变化，大量小规模、可持续的本地粮食生产系统可以帮助确保粮食安全，并有助于减少美国粮食供应对环境的影响。不幸的是，许多当地粮食生产（例如，后院花园）需要大量的投入，如水和肥料。缺乏有效的工具和技术来鼓励新手开始以可持续的方式种植自己的食物。这项工作将有助于实现长期粮食安全，并提供可用于应对其他可持续性挑战的经验、概念、方法和软件工具。此外，计算研究将提供一个可以推广到其他工作的例子，以更有效地整合分布在许多人身上的知识。

This project integrates research in computing and sustainability science with the goal of enabling a new approach to sustainable food security. The PIs propose to combine cyber-human systems and crowdsourcing research with the science of agroecology with two main research goals: 1) to develop an understanding of how online design tools may contribute to sustainability through enhanced local food production, and 2) to utilize the population of a plant species database as an instance of a class of problems amenable to intelligent crowdsourcing, and pioneer new knowledge in crowdsourcing optimization. As part of this project, the research team will design, build, deploy, and evaluate the Sustainable Polyculture Composer, an online software tool to aid in the design of small-scale plant-based agricultural ecosystems (e.g., back yard food forests). Long-term food security is central to sustainability. US food supply chains contribute to global change and are vulnerable to its impacts. Large numbers of small-scale, sustainable, local food production systems could help ensure food security in the face of global change, and could help reduce the environmental impacts of the US food supply. Unfortunately, many efforts at local food production (e.g., back yard gardens) require significant inputs such as water and fertilizer. Effective tools and techniques to encourage novices to begin growing their own food in sustainable ways are lacking. The work will contribute to long-term food security and offer lessons, concepts, methods, and software tools that may be transferable to other sustainability challenges. In addition, the computing research will provide an example that can be generalized to other efforts to more effectively integrate knowledge that is distributed across many people.