Multi-model predictions of ecosystem flux under climate change based on novel genetic and image analysis methods

基于新颖的遗传和图像分析方法的气候变化下生态系统通量的多模型预测

• 批准号: FS110200051
• 负责人: Prof Andrew Lowe
• 金额: $ 39.9万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: Super Science Fellowships
• 财政年份: 2011
• 资助国家: 澳大利亚
• 起止时间: 2011-09-24 至 2014-11-06
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FS110200051
• 关键词: Multi; model; predictions; ecosystem; flux

Improving the forecasts of ecosystem shifts must be a key focus of future ecological research if we are to preserve our unique Australian landscapes. Our proposal is of clear benefit to Australia because of the urgent need for integrated methods to predict the cumulative impact of shifts in climate and land use. We will also contribute innovative tools involving genetic and image analysis, and state-of-the-art modelling. The damage modern human societies are inflicting on global environments has led to a great demand for logistically feasible and cost-effective ways to prevent biodiversity loss.

如果我们要保护我们独特的澳大利亚景观，改善生态系统变化的预测必须是未来生态研究的关键重点。我们的建议显然对澳大利亚有利，因为迫切需要综合方法来预测气候和土地利用变化的累积影响。我们还将提供创新的工具，包括遗传和图像分析，以及最先进的建模。现代人类社会对全球环境造成的破坏导致了对防止生物多样性丧失的后勤上可行和成本效益高的方法的巨大需求。