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Revealing Long-Term Change in Vegetation Landscapes: The English Lake District and Beyond

揭示植被景观的长期变化：英国湖区及其他地区

基本信息

批准号：
AH/T006153/1
负责人：
Ian Gregory
金额：
$ 3.03万
依托单位：
Lancaster University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=AH%2FT006153%2F1
关键词：
Revealing Long Term Change Vegetation

项目摘要

Ecological restoration and re-wilding are common practices in the management of landscapes. Both of these approaches aim to restore past landscapes and, in doing so, enhance biodiversity. Unfortunately, whilst we have a good understanding of what past landscapes looked like, we have little idea of what the species were that inhabited those landscapes. Botanical surveys using modern scientific approaches did not start until around the 1960s and prior to this data is in disparate and descriptive sources which pose many challenges for scientists to use. The lack of readily accessible data makes it difficult to make management decisions regarding how habitats should be conserved or restored. In this project we will bring together academics from landscape history, digital humanities, and botany and conservation to address this challenge. Using approaches from digital humanities we can access a wide range of sources that are not easily accessible to botanists. We will utilise a corpus of over 300 texts that we have already assembled. In a series of workshops we will explore the major challenges involved in using this data appropriately and communicating its information to academics and non-academics who are interested in the landscapes of the present and the future. Over the course of the network we will use the workshops to develop and shade a series of exemplars of our techniques in action focusing on a small number of species in the Lake District.Our first workshop will focus on how we can extract species names from historical texts in digital form. This workshop will bring experts in natural language processing (NLP) and digital humanities techniques together with landscape historians to explore and apply approaches such as NLP, geographical information systems (GIS) and qualitative spatial representation (QSR) to address some of the challenges faced in understanding what species there were, and where and when they were recorded. Location is a particularly challenging as we must be able to cope with and combine both place names and other types of information such as "...on the lower slopes above Borrowdale." Our second workshop will focus on integrating these sources into the modelling approaches used in modern botany. Historians and botanists very rarely work together so this will be an excellent opportunity to bridge this disciplinary divide. One key challenge will be data accuracy, the implications of the limited and fragmented nature of our sources, on the so called 'recorder effort.' The final workshop will focus on novel ways to communicate this data bringing together experts from a range of disciplines together with stakeholders such as planners and representatives of the heritage sector. The workshop will report on the findings from the previous two workshops and explore how data can be best communicated to those who will find it most useful. It will also develop an agenda for publication and future grant applications to further develop the network.

生态恢复和野生化是景观管理的常见做法。这两种方法都旨在恢复过去的景观，从而增强生物多样性。不幸的是，虽然我们对过去的景观有了很好的了解，但我们对居住在这些景观中的物种知之甚少。使用现代科学方法的植物调查直到20世纪60年代左右才开始，在此之前，数据来自不同的描述性来源，这对科学家的使用构成了许多挑战。由于缺乏现成的数据，很难就如何保护或恢复生境作出管理决定。在这个项目中，我们将汇集景观历史、数字人文、植物学和保护方面的学者来应对这一挑战。使用数字人文学科的方法，我们可以访问植物学家不容易访问的广泛资源。我们将利用我们已经收集的300多个文本的语料库。在一系列的研讨会中，我们将探讨适当使用这些数据所涉及的主要挑战，并将其信息传达给对现在和未来的景观感兴趣的学者和非学者。在网络的过程中，我们将使用研讨会来开发和遮蔽一系列我们的技术范例，重点关注湖区的少数物种。我们的第一个研讨会将集中讨论如何从数字形式的历史文本中提取物种名称。本次研讨会将邀请自然语言处理（NLP）和数字人文技术方面的专家与景观历史学家一起探索和应用自然语言处理、地理信息系统（GIS）和定性空间表示（QSR）等方法，以解决在了解物种种类、记录地点和时间方面面临的一些挑战。位置是一个特别具有挑战性的问题，因为我们必须能够处理并结合地名和其他类型的信息，如“……在博罗代尔上方较低的山坡上。”我们的第二个研讨会将集中于将这些资源整合到现代植物学中使用的建模方法中。历史学家和植物学家很少在一起工作，所以这将是一个弥合这一学科分歧的绝佳机会。一个关键的挑战将是数据的准确性，即我们的信息来源的有限性和碎片性，对所谓的“记录努力”的影响。最后的研讨会将集中讨论交流这些数据的新方法，将来自不同学科的专家与遗产部门的规划者和代表等利益相关者聚集在一起。研讨会将报告前两次研讨会的结果，并探讨如何将数据最好地传达给最有用的人。它还将制定出版和未来拨款申请的议程，以进一步发展该网络。