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.

随着人们对昆虫重要性的认识不断提高，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造成严重后果。然而，知识上的差距限制了在了解变化的规模和方向方面取得进展。关于昆虫趋势的信息是零散的，时间序列数据在分类和空间上都是有限的和不具代表性的。此外，昆虫趋势和人为压力之间的因果关系尚未得到很好的确立。因此，很难评估有关“昆虫末日”的故事，理解生态系统的后果，制定缓解战略，或预测未来的趋势。为了解决这些不足，我们将汇集各种信息来源，如荟萃分析，相关关系和专家判断。GLiTRS将整理这些关于昆虫生物多样性如何响应人为压力而变化的不同证据，以及响应如何根据功能特征，空间和生物多样性指标而变化（例如物种丰度、占有率、丰富度和生物量），以及昆虫趋势如何推动进一步的变化我们将把这些证据整合到一个描述地球仪昆虫生物多样性趋势的威胁-响应模型中。该模型将以一系列概率陈述（贝叶斯信念网络）的形式表示，描述昆虫生物多样性和人为压力之间的关系。通过挑战这种“威胁-反应模型”来预测存在高质量时间序列数据的分类群和地方的趋势，我们将确定间接数据来源a）足以预测最近趋势，B）不足或c）太不确定的昆虫类群和地区。关于威胁-反应关系的可预测性的知识将允许预测--通过不确定性估计--全球所有主要分类群、功能群和生物群系的昆虫生物多样性如何变化。这种关于最近趋势的全球视角将为探索昆虫减少对一系列生态系统功能和服务的后果提供基础，以及生物多样性和生态系统特性如何可能受到未来环境变化的合理情景的影响。GLiTRS是一个雄心勃勃的创新研究计划：两个特点是特别突破性的。首先，多种形式的证据的整理将允许一个真正的全球性的角度来看昆虫的下降，这是无法实现的使用传统的方法。其次，通过验证“先验知识”（从证据合成）与最近的趋势，我们将评估昆虫下降的程度是可预测的，在什么规模。