Wings of change: using museum collections to forecast insect pollinator responses to climate change

昆虫在为作物和野花授粉方面发挥着关键作用，这意味着了解它们对气候变化的反应对于预测粮食安全和生态系统恢复力至关重要。种群可以以多种方式对环境变化作出反应，包括它们的行为，如物候学（出现等生活史事件的时间）和形态学（例如，机翼形状）。但这种反应可能会对生态系统产生重要的连锁反应，导致植物开花和传粉者出现等时间不匹配。然而，虽然生态学家理解这些后果的重要性，但工作主要限于过去30-40年的数据。缺乏气候变化前人口的历史数据限制了我们对应对措施进行机械建模的能力，使我们没有更长期的复苏背景，特别是在“异常”年份之后。因此，我们迫切需要从上个世纪早期的基线数据，如果我们要了解最近的主要气候和土地利用变化前后种群的物候和形态变化。在这个博士生项目中，你将通过研究过去150年收集的自然历史标本来解决这个问题。该项目将主要评估蝴蝶和蜜蜂对气候变化的反应，但也可能研究其他昆虫授粉分类群。为此，您将使用一个独特的大型数据集，包括来自英国各地的数万只数字化蜜蜂和数十万只蝴蝶，以及来自全球超过750个使用Symbiota数据平台的自然历史收藏的数据。您将使用标本标签信息和形态测量方法来了解功能性状反应，同时帮助开发生物信息学工具来收集这些信息。您将建立昆虫何时以及如何适应气候变化的机械模型，而不必改变它们的范围，并将其与已知的物种分布变化进行比较。使用这些模型，您将建立物种分布的准确预测，尤其是生态系统服务提供的准确预测，以帮助制定气候变化减缓规划。该项目将利用Pearse实验室已经开发的工具，以前用于根据零散的采集数据准确估计物候观察日期，并使用机器学习从图像中自动提取形态信息。您还将得到Gill实验室的支持，该实验室一直在整合英国蜜蜂数据集，并可以为许多蜜蜂和蝴蝶标本提供性状数据。吉尔在研究环境压力对昆虫传粉生态学的影响方面有经验，特别是了解蜜蜂的生活史。学生还将与其他昆虫授粉研究人员合作，包括Andres Arce博士，Jeff Ollerton教授，菲利普芬伯格博士和Ian巴恩斯教授

The critical role insects play in pollinating crops and wildflowers means understanding their responses to climate change is vital for predicting food security and ecosystem resilience. Populations can respond to environment variation in a number of ways, including their behaviour such as phenology (the timing of life-history events like emergence) and morphology (e.g., wing shape). But such responses can have important, cascading consequences for ecosystems, inducing mismatches in timing such as plant flowering and pollinator emergence. Yet whilst ecologists understand the significance of these consequences, work has been constrained to mostly data from the last 30-40 years. Lacking historic data about populations before climate change limits our ability to mechanistically model responses, leaving us without a longer-term context of recovery especially after 'outlier' years. Hence, we urgently require baseline data from the earlier part of the last century if we are to understand populations' phenological and morphological variation before and after the recent major climate and land-use changes.In this PhD studentship you will address this gap by studying natural history specimens collected over the past 150 years. The project will primarily assess butterfly and bee responses to climate change, but other insect pollinator taxa may be studied. To do this, you will be working with a unique and large dataset, including tens of thousands of digitised bees and hundreds of thousands of butterflies from across the UK, as well as data from the >750 natural history collections worldwide that use the Symbiota data platform. You will use specimen label information and morphometric approaches to understand functional trait responses, whilst helping to develop bioinformatic tools to gather this information. You will build mechanistic models of when and how insects can adapt to climate change without necessarily having to shift their ranges, and compare this to known species distribution changes. Using these models, you will build accurate forecasts of species' distributions and, critically, ecosystem service delivery, in order to help climate change mitigation planning.This project will leverage tools already developed by the Pearse lab previously used to accurately estimate phenological observation dates from patchy collections data, and to automatically extract morphological information from images using machine learning. You will also be supported by the Gill lab, who has been putting together the UK bee dataset and can provide trait data for many of the bee and butterfly specimens. Gill has experience in studying the effects of environmental stressors on insect pollinator ecology, and especially understanding bee life histories. The student will also get to collaborate with other insect pollinator researchers including Dr Andres Arce, Prof. Jeff Ollerton, Dr Phillip Fenberg, and Prof. Ian Barnes