GLobal Insect Threat-Response Synthesis (GLiTRS): a comprehensive and predictive assessment of the pattern and consequences of insect declines

全球昆虫威胁响应综合（GLiTRS）：对昆虫衰退模式和后果的全面预测评估

• 批准号: NE/V006886/1
• 负责人: John Jones
• 金额: $ 33.41万
• 依托单位: Queen Mary University of London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV006886%2F1
• 关键词: GLobal; Insect; Threat; Response; Synthesis

With increasing recognition of the importance of insects, there are growing concerns that insect biodiversity has declined globally, with serious consequences for ecosystem function and services. Yet, gaps in knowledge limit progress in understanding the magnitude and direction of change. Information about insect trends is fragmented, and time-series data are restricted and unrepresentative, both taxonomically and spatially. Moreover, causal links between insect trends and anthropogenic pressures are not well-established. It is, therefore, difficult to evaluate stories about "insectageddon", to understand the ecosystem consequences, to devise mitigation strategies, or predict future trends. To address the shortfalls, we will bring together diverse sources of information, such as meta-analyses, correlative relationships and expert judgement. GLiTRS will collate these diverse lines of evidence on how insect biodiversity has changed in response to anthropogenic pressures, how responses vary according to functional traits, over space, and across biodiversity metrics (e.g. species abundance, occupancy, richness and biomass), and how insect trends drive further changes (e.g. mediated by interaction networks).We will integrate these lines of evidence into a Threat-Response model describing trends in insect biodiversity across the globe. The model will be represented in the form of a series of probabilistic statements (a Bayesian belief network) describing relationships between insect biodiversity and anthropogenic pressures. By challenging this "Threat-Response model" to predict trends for taxa and places where high-quality time series data exist, we will identify insect groups and regions for which indirect data sources are a) sufficient for predicting recent trends, b) inadequate, or c) too uncertain. Knowledge about the predictability of threat-response relationships will allow projections - with uncertainty estimates - of how insect biodiversity has changed globally, across all major taxa, functional groups and biomes.This global perspective on recent trends will provide the basis for an exploration of the consequences of insect decline for a range of ecosystem functions and services, as well as how biodiversity and ecosystem properties might be affected by plausible scenarios of future environmental change.GLiTRS is an ambitious and innovative research program: two features are particularly ground-breaking. First, the collation of multiple forms of evidence will permit a truly global perspective on insect declines that is unachievable using conventional approaches. Second, by validating "prior knowledge" (from evidence synthesis) with recent trends, we will assess the degree to which insect declines are predictable, and at what scales.

随着对昆虫重要性的认识，人们越来越担心昆虫生物多样性在全球范围内下降，对生态系统功能和服务产生了严重的影响。然而，知识的差距限制了理解变化的幅度和方向的进展。有关昆虫趋势的信息是分散的，在分类和空间上，时间序列数据受到限制和无代表性。此外，昆虫趋势与人为压力之间的因果关系并不确定。因此，很难评估有关“昆虫虫”，了解生态系统后果，制定缓解策略或预测未来趋势的故事。为了解决这些短缺，我们将汇集各种信息来源，例如荟萃分析，相关关系和专家判断。 Glitrs将对昆虫生物多样性如何改变人为压力发生变化，响应如何根据功能性状，跨太空以及生物多样性指标（例如物种丰度，占用性，占用性，丰富性和生物量）来变化，以及昆虫趋势如何变化（例如，通过互动的建立来互动），这些证据将如何变化。全球昆虫生物多样性的趋势。该模型将以一系列概率陈述（贝叶斯信念网络）的形式表示，该模型描述了昆虫生物多样性与人为压力之间的关系。通过挑战这种“威胁响应模型”来预测存在高质量时间序列数据的趋势，我们将确定间接数据源的昆虫群体和区域A）足以预测最近的趋势，b）不足或C）过于不确定。关于威胁回应关系可预测性的知识将允许预测（具有不确定性估计），即昆虫生物多样性如何在全球，所有主要的分类群，功能组和生物群落中发生变化。这一全球视角将为探索昆虫范围的生态系统功能和生物范围的范围探索昆虫下降的影响提供基础环境变化。Glitrs是一项雄心勃勃的创新研究计划：两个特征尤其突破。首先，多种证据的整理将允许使用常规方法对昆虫下降的真正全球视角。其次，通过验证“先验知识”（从证据综合）以最近的趋势验证，我们将评估昆虫下降的可预测程度，以及在什么尺度上。