Open Knowledge Exchange (KE) Fellowships - Facilitating the application of decision support tools for habitat creation

世纪社会面临的最大挑战之一将是在避免环境退化的同时协调对土地使用的相互竞争的需求。粮食、淡水和能源的供应以及总体生活质量取决于生态系统的健康，而生态系统受到短视的土地管理做法和气候变化的威胁。物种和生态系统在气候变化中生存的能力有限，特别是在工业化的景观中，自然栖息地支离破碎，种群数量少，物种很难在新的气候适宜的地点定居。为了应对这一挑战，许多组织正在参与生态系统恢复，旨在建立一个功能强大的生态网络，以抵御未来的冲击。现有的野生动物保护区将构成这一网络的骨干，但其完成需要在广阔的空间范围内采取协调行动，涉及各种各样的土地使用者和土地所有者。决策支持工具对于综合复杂的空间数据和帮助确定有限资源的优先次序非常宝贵。有各种工具和数据来源可用于通知景观规模保护，其中一些来自NERC资助的科学。特别是，计算网络模型可以显示不同的栖息地安排如何最大限度地提高连通性或通过景观流动。其中一个例子是利物浦大学开发的由NERC资助的Condatis软件。从这些模型中获得信息输出需要准确的输入，其形式是生境和恢复潜力以及物种特征的地图。英国拥有令人羡慕的环境和物种数据收集，其中大部分由NERC资助，但访问和处理可能很复杂。Condatis项目和其他栖息地网络模型激发了利益相关者的极大热情和支持。然而，已经查明了在采用最佳工具方面的障碍，包括缺乏简明的英文文件、对在何种情况下使用何种软件感到困惑、缺乏可获取的数据以及缺乏显示在实地成功执行的产出的完整案例研究。景观规模项目的时间和资源有限是一个复杂的问题。该项目将建立一个网络，在英国和欧洲影响栖息地创造和恢复决策的研究人员和决策者之间进行实用知识交流。该研究金将首先侧重于增进对现有生境网络建模工具的了解，并提高对这些工具的认识。将通过创建网站、论坛和社交媒体来促进在线社区。基于用户反馈的文档将浓缩从成功项目中吸取的经验教训，并加速新用户的学习曲线。第二，合作伙伴将帮助确定物种和生境数据的来源，并探讨如何更方便地获取这些数据，用于生境网络模型。第三，实际支持将有助于少数使用Condatis的个案研究小规模举措在实地取得成果。这些案例研究将作为工作示例进行准备，以指导新用户并建立对Condatis作为决策工具的信心。由于这项研究金，许多相关的最终用户将更有能力在人居网络内优先采取行动。这样做的目的是使这种分析成为保护组织的主流，而不是专门针对组织内愿意投入数月时间进行分析工作的少数个人。如果发生这种情况，可以用最少的时间和金钱做出更合理的现实世界决策。最终的结果将是物种和生态功能在栖息地网络中得以维持，这些网络将为子孙后代提供弹性，为人类繁荣的多个方面做出贡献。

One of the biggest challenges for society in the 21st century will be to reconcile competing demands on land use while avoiding environmental degradation. Supplies of food, fresh water and energy and overall quality of life depend on the health of ecosystems, which are threatened by short-sighted land management practices and climate change. Species and ecosystems have limited capacity to survive climate change, especially in industrialised landscapes where natural habitats are fragmented, populations are small, and it is difficult for species to colonise sites that are newly climatically suitable.In response to this challenge, many organisations are getting involved in ecosystem restoration, and aim to build a functioning ecological network which will be resilient to future shocks. Existing wildlife sites will form the backbone of this network, but its completion requires coordinated action on a vast spatial scale, involving a hugely diverse body of land users and landowners. Decision support tools can be invaluable to synthesise complex, spatial data and help to prioritise limited resources. There are various tools and sources of data available for informing landscape scale conservation and a number stem from NERC-funded science. In particular, computational network models can show how different habitat arrangements might maximise connectivity or flow through the landscape. One example of this is the NERC-funded Condatis software developed at the University of Liverpool. Getting informative outputs from such models requires accurate inputs, in the form of maps of habitat and restoration potential, and species traits. The UK has enviable collections of environmental and species data, much funded by NERC, but it can be complex to access and process.The Condatis project and other habitat network models have catalysed great enthusiasm and support from stakeholders. However, barriers to uptake of the best tools have been identified, including a lack of plain English documentation, confusion about which software to use in which case, a lack of accessible data and a lack of completed case studies showing outputs successfully implemented on the ground. Limited time and resources within landscape scale projects is a compounding issue. This project will build a network for practical knowledge exchange between researchers and decision makers who influence habitat creation and restoration decisions in the UK and Europe. The fellowship will focus firstly on improving understanding of the existing habitat network modelling tools and increasing awareness of them. An online community will be fostered by creation of a website, forum and social media. Documentation based on user feedback will condense the lessons learned from successful projects and accelerate the learning curve for new users. Secondly, partners will help to identify sources of species and habitat data, and explore ways of delivering easier access to these data for use in habitat network models. Thirdly, practical support will assist a small number of case study landscape-scale initiatives using Condatis, to achieve results on the ground. These case studies will be prepared as worked examples to guide new users and build confidence in Condatis as a decision making tool. As a result of this fellowship, many relevant end-users will be better equipped to prioritise actions within habitat networks. The aim is that this type of analysis will become mainstream within conservation organisations, rather than specialised to a handful of individuals within organisations willing to invest months in analytical work. If this happens, more justifiable real-world decisions can be made with minimal overheads of time and money. The ultimate result will be that species and ecological functions are maintained in habitat networks that will be resilient for generations to come, contributing to multiple aspects of human prosperity.