Detecting and attributing biodiversity trends – drivers of past and future population and community dynamics in North American breeding birds (DEBTs)

债务的关键目标是开发和实施一种新的过程--显式集合模型框架，以检测、确定和预测生物多样性趋势。这一框架将有助于理清非生物和生物驱动因素对观察到的生物多样性变化的重要性，以便在全球变化的情况下做出更可靠的生物多样性预测。Debt将专注于北美繁殖鸟类数量的50年时间序列，作为一个独特的长期和地理范围广泛的数据集，这为比较历史数据的多模型表现以及量化最近环境变化和由此产生的未来殖民信用和灭绝债务的瞬时动态提供了理想的测试案例。明确的不确定性评估将查明不确定性的重要来源，并有助于指导未来的监测工作。该领域主要科学家参加的国际研究讲习班将综合从个案研究中获得的结果，并将制定一项议程，以便在分类组和区域之间实施区域陆地生物多样性模型相互比较。

The key aim of DEBTs is to develop and operationalise a new process-explicit ensemble model framework to detect, attribute and project biodiversity trends. This framework will allow disentangling the importance of abiotic and biotic drivers on observed biodiversity changes to make more robust biodiversity predictions under scenarios of global change. DEBTs will focus on a 50-year time series of North American breeding bird counts as a unique long-term and geographically broad data set, which provides an ideal test case for comparing multi-model performance on historic data and for quantifying transient dynamics from recent environmental change and resulting future colonisation credits and extinction debts. Explicit uncertainty assessments will pinpoint important sources of uncertainty and help guide future monitoring efforts. An international research workshop with leading scientists in the field will synthesise the results gained from the case study and will develop an agenda for implementing regional terrestrial biodiversity model intercomparisons across taxonomic groups and regions.