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Continuous monitoring of rainforest biodiversity via acoustic signal processing

通过声学信号处理持续监测雨林生物多样性

基本信息

批准号：
NE/L012456/1
负责人：
Robert Ewers
金额：
$ 18.45万
依托单位：
Imperial College London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2014
资助国家：
英国
起止时间：
2014 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FL012456%2F1
关键词：
Continuous monitoring rainforest biodiversity via

项目摘要

There is only limited knowledge of how biodiversity changes through time, yet understanding those changes represents one of the great challenges to ecology. Knowing exactly how biodiversity is changing is important for determining which species are endangered and which are not, and for creating accurate indices that can be used to assess how effectively conservation money has been spent. There is a direct analogue with climate change: only through detailed climate data from automated monitoring stations have scientists been able to determine the rate and likely future impact of changing global climates. Exactly the same is true of biodiversity: we require detailed data from automated monitoring stations to determine the magnitude of the current extinction crisis and to best target the limited amount of money available to counteract it.The principal explanation for our lack of knowledge is the labour costs associated with monitoring biodiversity. It is expensive to have trained scientists conducting field surveys, and the solution is to monitor biodiversity using technology rather than people. Our work will do this by automated processing of acoustic data. Sound carries substantial information about biodiversity, being used for navigation and communication by a wide range of taxa. Acoustic information can tell us a lot about which bats, grasshoppers, birds and amphibians are present in a given area. It has even been used to identify individuals, with some species such as gibbons and dolphins having calls that are distinct to every single animal in the population, much as people have distinctive voices and names. We are going to stream data from a solar-powered sound recording system through mobile networks to an automated computer processing facility that will decipher the environmental noise to tell us which species are contributing to that noise. Our work will be take place in the rainforests of Borneo, one of the world's most biodiverse habitats and one of the most challenging natural environments in which to work. If we can successfully use technology to automatically record biodiversity here, then we can do it anywhere.We're going to combine our research with a free public radio station to be broadcast online, providing the public with a direct line to the rainforest itself. We hope that giving people the opportunity we have had of waking up to the sound of gibbons whooping to each other and the laughing calls of rhinoceros hornbills whomping past overhead will help convince them that, although rainforests are a long way away, they are beautiful environments that can be enjoyed even from afar.

关于生物多样性如何随着时间的推移而变化的知识有限，但了解这些变化是生态学面临的最大挑战之一。确切地了解生物多样性是如何变化的，对于确定哪些物种濒临灭绝，哪些物种没有，以及创建可用于评估保护资金使用效率的准确指数非常重要。气候变化有一个直接的类比：只有通过自动监测站提供的详细气候数据，科学家才能够确定全球气候变化的速度和未来可能产生的影响。生物多样性也是如此：我们需要自动化监测站提供的详细数据，以确定当前灭绝危机的严重程度，并最好地利用有限的资金来应对这一危机。我们缺乏知识的主要原因是与监测生物多样性有关的劳动力成本。让训练有素的科学家进行实地调查是昂贵的，解决办法是利用技术而不是人力来监测生物多样性。我们的工作将通过自动处理声学数据来实现这一点。声音携带着关于生物多样性的大量信息，被广泛的分类群用于导航和通信。声学信息可以告诉我们很多关于蝙蝠，蚱蜢，鸟类和两栖动物存在于一个给定的区域。它甚至被用来识别个体，一些物种，如长臂猿和海豚，其叫声与种群中的每一种动物都不同，就像人有独特的声音和名字一样。我们将通过移动的网络把来自太阳能录音系统的数据传输到一个自动化的计算机处理设备上，这个设备将破译环境噪音，告诉我们哪些物种对噪音有贡献。我们的工作将在婆罗洲的热带雨林中进行，婆罗洲是世界上生物多样性最丰富的栖息地之一，也是最具挑战性的自然环境之一。如果我们能成功地利用技术自动记录这里的生物多样性，那么我们就可以在任何地方这样做。我们将把我们的研究与一个免费的公共广播电台结合起来，在网上广播，为公众提供一条直达雨林本身的线路。我们希望，让人们有机会在长臂猿的叫声和犀牛犀鸟的笑声中醒来，这将有助于说服他们，虽然雨林离我们很远，但它们是美丽的环境，即使在远处也可以享受。