Forecasting Future Invasions and their Impacts (FFII)

预测未来的入侵及其影响（FFII）

• 批准号: 243876372
• 负责人: Professor Dr. Jonathan Jeschke
• 金额: --
• 依托单位: Leibniz-Institut für Gewässerökologie und Binnenfischerei (IGB)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2013
• 资助国家: 德国
• 起止时间: 2012-12-31 至 2017-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/243876372?language=en
• 关键词: Forecasting; Future; Invasions; their; Impacts

It is now widely accepted that prevention and early responses are the best strategies to mitigate the impacts of invasive alien species (IAS). Consequently, research efforts must focus on prediction, both of the likely distribution of invasions and of invader impact in newly invaded areas. Accounting for global environmental changes is obviously crucial for these predictions. It is also important to combine our understanding of broad-scale patterns from global studies with our understanding of finer scale and more detailed mechanisms from specific communities. Our overall objectives are to better forecast the future of invasions and their impacts worldwide. For these predictions, we will use analyses focusing on (a) the patterns, (b) the processes, (c) the impacts and (d) the future of biological invasions. The DFG-funded part of the project will also cover all of these aspects, with a focus on macroecological analyses, using the IUCN list of 100 of the World's Worst Invasive Species, the list of the 800 IAS in the Global Invasive Species Database (GISD), and the 60 000 IUCN Red-Listed species. We will re-classify the current impact categories in the GISD and apply the new categorization to all IAS in this GISD database. Combining these two points will permit us to assess patterns in global spread and impact of the IAS worldwide, providing a global assessment of the future impact of IAS on the 60,000 species in the IUCN Red List Database. For this effort, we will benefit from access to both the IUCN Red List and Global Invasive Species Database to interlink the two databases, through a tight collaboration with IUCN and ISSG as privileged stakeholders. We will complete this approach by studying the finer scale of ecological communities, using as an animal model a large and homogeneous taxonomic group, the Formicidae (ants). In this regard, we will aim at incorporating ecological components to complement our bioclimatic modelling approaches to predict the future distribution of these species, as well as the mechanisms and magnitude of their likely impact in invaded areas.

现在人们普遍认为，预防和早期反应是减轻外来入侵物种影响的最佳战略。因此，研究工作必须集中在预测，既可能分布的入侵和入侵者的影响，在新入侵的地区。考虑到全球环境变化显然对这些预测至关重要。联合收割机还必须将我们从全球研究中对大规模模式的理解与我们从特定社区中对更细规模和更详细机制的理解结合起来。我们的总体目标是更好地预测入侵的未来及其在世界范围内的影响。对于这些预测，我们将使用分析集中在（a）模式，（B）过程，（c）影响和（d）生物入侵的未来。DFG资助的项目部分也将涵盖所有这些方面，重点是宏观生态分析，使用世界自然保护联盟的100种世界上最严重的入侵物种名单，全球入侵物种数据库（GISD）中的800种IAS名单，以及60，000种世界自然保护联盟红名单物种。我们将重新分类GISD中的当前影响类别，并将新的分类应用于GISD数据库中的所有IAS。结合这两点将使我们能够评估IAS在全球范围内的传播模式和影响，提供IAS对IUCN红色名录数据库中60，000种物种未来影响的全球评估。为此，我们将通过与IUCN和ISSG作为特权利益相关者的密切合作，从IUCN红色名录和全球入侵物种数据库中受益，以将两个数据库相互链接。我们将通过研究生态群落的更精细尺度来完成这种方法，使用大型和同质的分类组，蚁科（蚂蚁）作为动物模型。在这方面，我们的目标是纳入生态组成部分，以补充我们的生物气候建模方法，以预测这些物种的未来分布，以及它们在入侵地区可能产生的影响的机制和程度。