A predictive framework for invaded communities

被入侵社区的预测框架

• 批准号: DP150103017
• 负责人: Prof Melodie McGeoch
• 金额: $ 27.53万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2015
• 资助国家: 澳大利亚
• 起止时间: 2015-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP150103017
• 关键词: predictive; framework; invaded; communities

Australian native and agricultural landscapes are under threat from introduced plant species. Over $1.5 billion per year is spent on subsequent land management. However it is not clear that this is money is well spent. This project aims to determine the importance of the two major factors (dispersal and habitat) that drive the invasion of Australian native plant communities by surveying native Australian plant communities with different levels of disturbance and numbers of introduced species. The results could enable the building and testing of an innovative model for predicting the establishment and spread of invasive species. This critical research could help target money towards better management of invasive species in native environments.

澳大利亚的本土和农业景观正受到引进植物物种的威胁。每年用于随后的土地管理的费用超过15亿美元。然而，目前尚不清楚这笔钱是否花得值。该项目旨在通过调查具有不同干扰水平和引入物种数量的澳大利亚本土植物群落，确定推动澳大利亚本土植物群落入侵的两个主要因素（扩散和栖息地）的重要性。研究结果可以建立和测试一个创新模型，用于预测入侵物种的建立和传播。这项关键研究可以帮助将资金用于更好地管理本土环境中的入侵物种。