Monitoring species to establish presence/absence and population size is expensive and time-consuming, yet crucial when studying the impacts of climate change on terrestrial ecosystems. Automatic acoustic observatories (AAO) are devices that passively collect and classify sounds to enable species identification in the field but they must be trained prior to going into the field.
This project aims to achieve a step change in AAOs by adding evolutionary knowledge of acoustic communication to identify species without prior training. This will be a practical, cost-effective and powerful way to establish species presence/absence in areas without extensive fieldwork, and continuously monitor a range of ecological environments without prior knowledge of species occupation. This will open up new opportunities for research in sensory ecology, augmenting traditional approaches, which will lead to novel solutions to ecological problems.
Our aim is to develop and field-test technology that will enable the automated continuous monitoring of acoustic communities in a non-invasive and low cost way. We will focus on Orthoptera song (grasshoppers, crickets and bush-crickets) as a model system but in the longer term these techniques will be applicable across a wide range of acoustically communicating organisms. We will develop comparative analyses of Orthoptera song to inform the development of automatic acoustic observatories, which will then be field-tested to assess performance before dissemination. This will be achieved by pursuing a number of research objectives including the design of AAO devices, describe evolutionary relationships of Orthoptera and the evolution of song and to test systems in the field.
The project is multidisciplinary involving academics and researchers in three departments at York: Electronic Engineering, Biology and Environment and Geography.