Using food web theory to conserve ecosystems

利用食物网理论保护生态系统

• 批准号: DE140101477
• 负责人: Prof Eve McDonald-Madden
• 金额: $ 25.94万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-01-11 至 2017-04-14
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE140101477
• 关键词: Using; food; web; theory; conserve

Species interact with each other and the management of one species can impact on other species. These interactions are often ignored in conservation decision making. Food web theory is the obvious basis for considering links between species when making conservation decisions, but actually contains little explicit guidance for the management of multiple species. Using a novel application of optimisation approaches pioneered in artificial intelligence research, we aim to demonstrate how food web theory can guide the management of multiple species. In doing so, we will also test the effectiveness of widely used approaches to multi-species management, such as keystone species, umbrella species and bottom-up control.

物种之间相互影响，一个物种的管理会影响其他物种。这些相互作用往往被忽视的保护决策。食物网理论是在做出保护决策时考虑物种之间联系的明显基础，但实际上对多个物种的管理几乎没有明确的指导。使用人工智能研究中开创的优化方法的新应用，我们的目标是展示食物网理论如何指导多个物种的管理。在此过程中，我们还将测试广泛使用的多物种管理方法的有效性，例如关键物种，伞型物种和自下而上的控制。